2011
Balasingam, Balakumar; Bolic, Miodrag; Djuric, Petar M; Miguez, Joaquin
Efficient Distributed Resampling for Particle Filters Artículo en actas
En: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3772–3775, IEEE, Prague, 2011, ISSN: 1520-6149.
Resumen | Enlaces | BibTeX | Etiquetas: Approximation algorithms, Copper, Covariance matrix, distributed resampling, Markov processes, Probability density function, Sequential Monte-Carlo methods, Signal processing, Signal processing algorithms
@inproceedings{Balasingam2011,
title = {Efficient Distributed Resampling for Particle Filters},
author = {Balakumar Balasingam and Miodrag Bolic and Petar M Djuric and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5947172},
issn = {1520-6149},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages = {3772--3775},
publisher = {IEEE},
address = {Prague},
abstract = {In particle filtering, resampling is the only step that cannot be fully parallelized. Recently, we have proposed algorithms for distributed resampling implemented on architectures with concurrent processing elements (PEs). The objective of distributed resampling is to reduce the communication among the PEs while not compromising the performance of the particle filter. An additional objective for implementation is to reduce the communication among the PEs. In this paper, we report an improved version of the distributed resampling algorithm that optimally selects the particles for communication between the PEs of the distributed scheme. Computer simulations are provided that demonstrate the improved performance of the proposed algorithm.},
keywords = {Approximation algorithms, Copper, Covariance matrix, distributed resampling, Markov processes, Probability density function, Sequential Monte-Carlo methods, Signal processing, Signal processing algorithms},
pubstate = {published},
tppubtype = {inproceedings}
}
In particle filtering, resampling is the only step that cannot be fully parallelized. Recently, we have proposed algorithms for distributed resampling implemented on architectures with concurrent processing elements (PEs). The objective of distributed resampling is to reduce the communication among the PEs while not compromising the performance of the particle filter. An additional objective for implementation is to reduce the communication among the PEs. In this paper, we report an improved version of the distributed resampling algorithm that optimally selects the particles for communication between the PEs of the distributed scheme. Computer simulations are provided that demonstrate the improved performance of the proposed algorithm.
Ruiz, Francisco J R; Perez-Cruz, Fernando
Zero-Error Codes for the Noisy-Typewriter Channel Artículo en actas
En: 2011 IEEE Information Theory Workshop, pp. 495–497, IEEE, Paraty, 2011, ISBN: 978-1-4577-0437-6.
Resumen | Enlaces | BibTeX | Etiquetas: channel capacity, Channel Coding, Equations, Linear code, Noise measurement, noisy-typewriter channel, nontrivial codes, nonzero zero-error rate, odd-letter noisy-typewriter channels, Upper bound, Vectors, zero-error capacity, zero-error codes
@inproceedings{Ruiz2011,
title = {Zero-Error Codes for the Noisy-Typewriter Channel},
author = {Francisco J R Ruiz and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6089510},
isbn = {978-1-4577-0437-6},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE Information Theory Workshop},
pages = {495--497},
publisher = {IEEE},
address = {Paraty},
abstract = {In this paper, we propose nontrivial codes that achieve a non-zero zero-error rate for several odd-letter noisy-typewriter channels. Some of these codes (specifically, those which are defined for a number of letters of the channel of the form 2n + 1) achieve the best-known lower bound on the zero-error capacity. We build the codes using linear codes over rings, as we do not require the multiplicative inverse to build the codes.},
keywords = {channel capacity, Channel Coding, Equations, Linear code, Noise measurement, noisy-typewriter channel, nontrivial codes, nonzero zero-error rate, odd-letter noisy-typewriter channels, Upper bound, Vectors, zero-error capacity, zero-error codes},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we propose nontrivial codes that achieve a non-zero zero-error rate for several odd-letter noisy-typewriter channels. Some of these codes (specifically, those which are defined for a number of letters of the channel of the form 2n + 1) achieve the best-known lower bound on the zero-error capacity. We build the codes using linear codes over rings, as we do not require the multiplicative inverse to build the codes.
Koch, Tobias; Lapidoth, Amos
Asymmetric Quantizers are Better at Low SNR Artículo en actas
En: 2011 IEEE International Symposium on Information Theory Proceedings, pp. 2592–2596, IEEE, St. Petersburg, 2011, ISSN: 2157-8095.
Resumen | Enlaces | BibTeX | Etiquetas: asymmetric one-bit quantizer, asymmetric signal constellations, channel capacity, Channel Coding, Constellation diagram, Decoding, discrete-time average-power-limited Gaussian chann, Gaussian channels, quantization, Signal to noise ratio, signal-to-noise ratio, SNR, spread spectrum communication, spread-spectrum communications, ultra wideband communication, ultrawideband communications, Upper bound
@inproceedings{Koch2011,
title = {Asymmetric Quantizers are Better at Low SNR},
author = {Tobias Koch and Amos Lapidoth},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6034037},
issn = {2157-8095},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE International Symposium on Information Theory Proceedings},
pages = {2592--2596},
publisher = {IEEE},
address = {St. Petersburg},
abstract = {We study the behavior of channel capacity when a one-bit quantizer is employed at the output of the discrete-time average-power-limited Gaussian channel. We focus on the low signal-to-noise ratio regime, where communication at very low spectral efficiencies takes place, as in Spread-Spectrum and Ultra-Wideband communications. It is well known that, in this regime, a symmetric one-bit quantizer reduces capacity by 2/$pi$, which translates to a power loss of approximately two decibels. Here we show that if an asymmetric one-bit quantizer is employed, and if asymmetric signal constellations are used, then these two decibels can be recovered in full.},
keywords = {asymmetric one-bit quantizer, asymmetric signal constellations, channel capacity, Channel Coding, Constellation diagram, Decoding, discrete-time average-power-limited Gaussian chann, Gaussian channels, quantization, Signal to noise ratio, signal-to-noise ratio, SNR, spread spectrum communication, spread-spectrum communications, ultra wideband communication, ultrawideband communications, Upper bound},
pubstate = {published},
tppubtype = {inproceedings}
}
We study the behavior of channel capacity when a one-bit quantizer is employed at the output of the discrete-time average-power-limited Gaussian channel. We focus on the low signal-to-noise ratio regime, where communication at very low spectral efficiencies takes place, as in Spread-Spectrum and Ultra-Wideband communications. It is well known that, in this regime, a symmetric one-bit quantizer reduces capacity by 2/$pi$, which translates to a power loss of approximately two decibels. Here we show that if an asymmetric one-bit quantizer is employed, and if asymmetric signal constellations are used, then these two decibels can be recovered in full.
Olmos, Pablo M; Urbanke, Rudiger
Scaling Behavior of Convolutional LDPC Ensembles over the BEC Artículo en actas
En: 2011 IEEE International Symposium on Information Theory Proceedings, pp. 1816–1820, IEEE, Saint Petersburg, 2011, ISSN: 2157-8095.
Resumen | Enlaces | BibTeX | Etiquetas: BEC, binary codes, binary erasure channel, Bit error rate, convolutional codes, convolutional LDPC ensembles, coupled sparse graph codes, Couplings, Decoding, error probability, Iterative decoding, parity check codes, scaling behavior
@inproceedings{Olmos2011,
title = {Scaling Behavior of Convolutional LDPC Ensembles over the BEC},
author = {Pablo M Olmos and Rudiger Urbanke},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6033863},
issn = {2157-8095},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE International Symposium on Information Theory Proceedings},
pages = {1816--1820},
publisher = {IEEE},
address = {Saint Petersburg},
abstract = {We study the scaling behavior of coupled sparse graph codes over the binary erasure channel. In particular, let 2L+1 be the length of the coupled chain, let M be the number of variables in each of the 2L+1 local copies, let ℓ be the number of iterations, let Pb denote the bit error probability, and let ∈ denote the channel parameter. We are interested in how these quantities scale when we let the blocklength (2L + 1)M tend to infinity. Based on empirical evidence we show that the threshold saturation phenomenon is rather stable with respect to the scaling of the various parameters and we formulate some general rules of thumb which can serve as a guide for the design of coding systems based on coupled graphs.},
keywords = {BEC, binary codes, binary erasure channel, Bit error rate, convolutional codes, convolutional LDPC ensembles, coupled sparse graph codes, Couplings, Decoding, error probability, Iterative decoding, parity check codes, scaling behavior},
pubstate = {published},
tppubtype = {inproceedings}
}
We study the scaling behavior of coupled sparse graph codes over the binary erasure channel. In particular, let 2L+1 be the length of the coupled chain, let M be the number of variables in each of the 2L+1 local copies, let ℓ be the number of iterations, let Pb denote the bit error probability, and let ∈ denote the channel parameter. We are interested in how these quantities scale when we let the blocklength (2L + 1)M tend to infinity. Based on empirical evidence we show that the threshold saturation phenomenon is rather stable with respect to the scaling of the various parameters and we formulate some general rules of thumb which can serve as a guide for the design of coding systems based on coupled graphs.
Taborda, Camilo G; Perez-Cruz, Fernando
Information Theory Concepts and their Relationship with the Bregman Loss Functions Artículo en actas
En: Workshop on Topics in Information Theory and Communications (WTITC’11), Porto, 2011.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Taborda2011,
title = {Information Theory Concepts and their Relationship with the Bregman Loss Functions},
author = {Camilo G Taborda and Fernando Perez-Cruz},
url = {http://www.it.pt/auto_temp_web_page_preview.asp?id=961},
year = {2011},
date = {2011-01-01},
booktitle = {Workshop on Topics in Information Theory and Communications (WTITC’11)},
address = {Porto},
abstract = {Among the past eight years the information theory has become interested in the exploration of links between the information and estimation theory. The best known results show how the mean square error and the mutual information between two random variables (input and output) over a Gaussian channel can be related. Similar results illustrate that, for the Poisson channel, exists different loss functions that can be associated with information theory concepts such as the mutual information and the relative entropy. The talk is oriented in the following way; initially we analyzed different properties that share the mean square error and its counterparts for the Poisson channel. Some results obtained early by the research community can be seen as consequences of the behavior of the analyzed loss functions. In addition, we present a broader version of the results obtained previously for both channels, we also establish the behavior of the mutual information between two random variables when the conditional distribution of the channel comes from the exponential family. One of the main issues explored along the talk is determining in which cases the loss function involved in the behavior of the mutual information corresponds to a Bregman Loss Function, situation that enable us to establish geometrical properties of the found relations},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Among the past eight years the information theory has become interested in the exploration of links between the information and estimation theory. The best known results show how the mean square error and the mutual information between two random variables (input and output) over a Gaussian channel can be related. Similar results illustrate that, for the Poisson channel, exists different loss functions that can be associated with information theory concepts such as the mutual information and the relative entropy. The talk is oriented in the following way; initially we analyzed different properties that share the mean square error and its counterparts for the Poisson channel. Some results obtained early by the research community can be seen as consequences of the behavior of the analyzed loss functions. In addition, we present a broader version of the results obtained previously for both channels, we also establish the behavior of the mutual information between two random variables when the conditional distribution of the channel comes from the exponential family. One of the main issues explored along the talk is determining in which cases the loss function involved in the behavior of the mutual information corresponds to a Bregman Loss Function, situation that enable us to establish geometrical properties of the found relations
Goparaju, S; Calderbank, A R; Carson, W R; Rodrigues, Miguel R D; Perez-Cruz, Fernando
When to Add Another Dimension when Communicating over MIMO Channels Artículo en actas
En: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3100–3103, IEEE, Prague, 2011, ISSN: 1520-6149.
Resumen | Enlaces | BibTeX | Etiquetas: divide and conquer approach, divide and conquer methods, error probability, error rate, error statistics, Gaussian channels, Lattices, Manganese, MIMO, MIMO channel, MIMO communication, multiple input multiple output Gaussian channel, Mutual information, optimal power allocation, power allocation, power constraint, receive filter, Resource management, Signal to noise ratio, signal-to-noise ratio, transmit filter, Upper bound
@inproceedings{Goparaju2011,
title = {When to Add Another Dimension when Communicating over MIMO Channels},
author = {S Goparaju and A R Calderbank and W R Carson and Miguel R D Rodrigues and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5946351},
issn = {1520-6149},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages = {3100--3103},
publisher = {IEEE},
address = {Prague},
abstract = {This paper introduces a divide and conquer approach to the design of transmit and receive filters for communication over a Multiple Input Multiple Output (MIMO) Gaussian channel subject to an average power constraint. It involves conversion to a set of parallel scalar channels, possibly with very different gains, followed by coding per sub-channel (i.e. over time) rather than coding across sub-channels (i.e. over time and space). The loss in performance is negligible at high signal-to-noise ratio (SNR) and not significant at medium SNR. The advantages are reduction in signal processing complexity and greater insight into the SNR thresholds at which a channel is first allocated power. This insight is a consequence of formulating the optimal power allocation in terms of an upper bound on error rate that is determined by parameters of the input lattice such as the minimum distance and kissing number. The resulting thresholds are given explicitly in terms of these lattice parameters. By contrast, when the optimization problem is phrased in terms of maximizing mutual information, the solution is mercury waterfilling, and the thresholds are implicit.},
keywords = {divide and conquer approach, divide and conquer methods, error probability, error rate, error statistics, Gaussian channels, Lattices, Manganese, MIMO, MIMO channel, MIMO communication, multiple input multiple output Gaussian channel, Mutual information, optimal power allocation, power allocation, power constraint, receive filter, Resource management, Signal to noise ratio, signal-to-noise ratio, transmit filter, Upper bound},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper introduces a divide and conquer approach to the design of transmit and receive filters for communication over a Multiple Input Multiple Output (MIMO) Gaussian channel subject to an average power constraint. It involves conversion to a set of parallel scalar channels, possibly with very different gains, followed by coding per sub-channel (i.e. over time) rather than coding across sub-channels (i.e. over time and space). The loss in performance is negligible at high signal-to-noise ratio (SNR) and not significant at medium SNR. The advantages are reduction in signal processing complexity and greater insight into the SNR thresholds at which a channel is first allocated power. This insight is a consequence of formulating the optimal power allocation in terms of an upper bound on error rate that is determined by parameters of the input lattice such as the minimum distance and kissing number. The resulting thresholds are given explicitly in terms of these lattice parameters. By contrast, when the optimization problem is phrased in terms of maximizing mutual information, the solution is mercury waterfilling, and the thresholds are implicit.
Leiva-Murillo, Jose M; Artés-Rodríguez, Antonio; Baca-García, Enrique
Visualization and Prediction of Disease Interactions with Continuous-Time Hidden Markov Models Artículo en actas
En: NIPS 2011 Workshop on Personalized Medicine., Sierra Nevada, 2011.
Resumen | Enlaces | BibTeX | Etiquetas: Computational, Information-Theoretic Learning with Statistics, Theory & Algorithms
@inproceedings{Leiva-Murillo2011,
title = {Visualization and Prediction of Disease Interactions with Continuous-Time Hidden Markov Models},
author = {Jose M Leiva-Murillo and Antonio Art\'{e}s-Rodr\'{i}guez and Enrique Baca-Garc\'{i}a},
url = {http://eprints.pascal-network.org/archive/00009110/},
year = {2011},
date = {2011-01-01},
booktitle = {NIPS 2011 Workshop on Personalized Medicine.},
address = {Sierra Nevada},
abstract = {This paper describes a method for discovering disease relationships and the evolution of diseases from medical records. The method makes use of continuous-time Markov chain models that overcome some drawbacks of the more widely used discrete-time chain models. The model addresses uncertainty in the diagnoses, possible diagnosis errors and the existence of multiple alternative diagnoses in the records. A set of experiments, performed on a dataset of psychiatric medical records, shows the capability of the model to visualize maps of comorbidity and causal interactions among diseases as well as to perform predictions of future evolution of diseases.},
keywords = {Computational, Information-Theoretic Learning with Statistics, Theory \& Algorithms},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper describes a method for discovering disease relationships and the evolution of diseases from medical records. The method makes use of continuous-time Markov chain models that overcome some drawbacks of the more widely used discrete-time chain models. The model addresses uncertainty in the diagnoses, possible diagnosis errors and the existence of multiple alternative diagnoses in the records. A set of experiments, performed on a dataset of psychiatric medical records, shows the capability of the model to visualize maps of comorbidity and causal interactions among diseases as well as to perform predictions of future evolution of diseases.
Olmos, Pablo M; Salamanca, Luis; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando
An Application of Tree-Structured Expectation Propagation for Channel Decoding Artículo en actas
En: Neural Information Processing Systems Foundation (NIPS), Granada, 2011.
@inproceedings{Olmos2011a,
title = {An Application of Tree-Structured Expectation Propagation for Channel Decoding},
author = {Pablo M Olmos and Luis Salamanca and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},
year = {2011},
date = {2011-01-01},
booktitle = {Neural Information Processing Systems Foundation (NIPS)},
address = {Granada},
abstract = {We show an application of a tree structure for approximate inference in graphical models using the expectation propagation algorithm. These approximations are typically used over graphs with short-range cycles. We demonstrate that these approximations also help in sparse graphs with long-range loops, as the ones used in coding theory to approach channel capacity. For asymptotically large sparse graph, the expectation propagation algorithm together with the tree structure yields a completely disconnected approximation to the graphical model but, for for finite-length practical sparse graphs, the tree structure approximation to the code graph provides accurate estimates for the marginal of each variable. Furthermore, we propose a new method for constructing the tree structure on the fly that might be more amenable for sparse graphs with general factors.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We show an application of a tree structure for approximate inference in graphical models using the expectation propagation algorithm. These approximations are typically used over graphs with short-range cycles. We demonstrate that these approximations also help in sparse graphs with long-range loops, as the ones used in coding theory to approach channel capacity. For asymptotically large sparse graph, the expectation propagation algorithm together with the tree structure yields a completely disconnected approximation to the graphical model but, for for finite-length practical sparse graphs, the tree structure approximation to the code graph provides accurate estimates for the marginal of each variable. Furthermore, we propose a new method for constructing the tree structure on the fly that might be more amenable for sparse graphs with general factors.
Olmos, Pablo M; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando
Capacity Achieving LDPC Ensembles for the TEP Decoder in Erasure Channels Artículo en actas
En: 2011 IEEE International Symposium on Information Theory Proceedings, pp. 2398–2402, IEEE, St. Petersburg, 2011, ISSN: 2157-8095.
Resumen | Enlaces | BibTeX | Etiquetas: BP threshold, Complexity theory, Decoding, Differential equations, erasure channels, fixed-rate code, Iterative decoding, LDPC, low-density parity-check codes, MAP capacity, MAP threshold, optimisation, Optimization, optimization problem, parity check codes, TEP decoder, tree-expectation propagation decoder
@inproceedings{Olmos2011b,
title = {Capacity Achieving LDPC Ensembles for the TEP Decoder in Erasure Channels},
author = {Pablo M Olmos and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6033993},
issn = {2157-8095},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE International Symposium on Information Theory Proceedings},
pages = {2398--2402},
publisher = {IEEE},
address = {St. Petersburg},
abstract = {In this work we address the design of degree distributions (DD) of low-density parity-check (LDPC) codes for the tree-expectation propagation (TEP) decoder. The optimization problem to find distributions to maximize the TEP decoding threshold for a fixed-rate code can not be analytically solved. We derive a simplified optimization problem that can be easily solved since it is based in the analytic expressions of the peeling decoder. Two kinds of solutions are obtained from this problem: we either design LDPC ensembles for which the BP threshold equals the MAP threshold or we get LDPC ensembles for which the TEP threshold outperforms the BP threshold, even achieving the MAP capacity in some cases. Hence, we proved that there exist ensembles for which the MAP solution can be obtained with linear complexity even though the BP threshold does not achieve the MAP threshold.},
keywords = {BP threshold, Complexity theory, Decoding, Differential equations, erasure channels, fixed-rate code, Iterative decoding, LDPC, low-density parity-check codes, MAP capacity, MAP threshold, optimisation, Optimization, optimization problem, parity check codes, TEP decoder, tree-expectation propagation decoder},
pubstate = {published},
tppubtype = {inproceedings}
}
In this work we address the design of degree distributions (DD) of low-density parity-check (LDPC) codes for the tree-expectation propagation (TEP) decoder. The optimization problem to find distributions to maximize the TEP decoding threshold for a fixed-rate code can not be analytically solved. We derive a simplified optimization problem that can be easily solved since it is based in the analytic expressions of the peeling decoder. Two kinds of solutions are obtained from this problem: we either design LDPC ensembles for which the BP threshold equals the MAP threshold or we get LDPC ensembles for which the TEP threshold outperforms the BP threshold, even achieving the MAP capacity in some cases. Hence, we proved that there exist ensembles for which the MAP solution can be obtained with linear complexity even though the BP threshold does not achieve the MAP threshold.
Asyhari, Taufiq A; Koch, Tobias; i Fàbregas, Albert Guillén
Nearest Neighbour Decoding and Pilot-Aided Channel Estimation in Stationary Gaussian Flat-Fading Channels Artículo en actas
En: 2011 IEEE International Symposium on Information Theory Proceedings, pp. 2786–2790, IEEE, St. Petersburg, 2011, ISSN: 2157-8095.
Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, Decoding, Fading, fading channels, Gaussian channels, MIMO, MIMO communication, MISO, multiple-input multiple-output, nearest neighbour decoding, noncoherent multiple-input single-output, pilot-aided channel estimation, Receiving antennas, Signal to noise ratio, signal-to-noise ratio, SNR, stationary Gaussian flat-fading channels, Wireless communication
@inproceedings{Asyhari2011,
title = {Nearest Neighbour Decoding and Pilot-Aided Channel Estimation in Stationary Gaussian Flat-Fading Channels},
author = {Taufiq A Asyhari and Tobias Koch and Albert Guill\'{e}n i F\`{a}bregas},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6034081},
issn = {2157-8095},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE International Symposium on Information Theory Proceedings},
pages = {2786--2790},
publisher = {IEEE},
address = {St. Petersburg},
abstract = {We study the information rates of non-coherent, stationary, Gaussian, multiple-input multiple-output (MIMO) flat-fading channels that are achievable with nearest neighbour decoding and pilot-aided channel estimation. In particular, we analyse the behaviour of these achievable rates in the limit as the signal-to-noise ratio (SNR) tends to infinity. We demonstrate that nearest neighbour decoding and pilot-aided channel estimation achieves the capacity pre-log-which is defined as the limiting ratio of the capacity to the logarithm of SNR as the SNR tends to infinity-of non-coherent multiple-input single-output (MISO) flat-fading channels, and it achieves the best so far known lower bound on the capacity pre-log of non-coherent MIMO flat-fading channels.},
keywords = {Channel estimation, Decoding, Fading, fading channels, Gaussian channels, MIMO, MIMO communication, MISO, multiple-input multiple-output, nearest neighbour decoding, noncoherent multiple-input single-output, pilot-aided channel estimation, Receiving antennas, Signal to noise ratio, signal-to-noise ratio, SNR, stationary Gaussian flat-fading channels, Wireless communication},
pubstate = {published},
tppubtype = {inproceedings}
}
We study the information rates of non-coherent, stationary, Gaussian, multiple-input multiple-output (MIMO) flat-fading channels that are achievable with nearest neighbour decoding and pilot-aided channel estimation. In particular, we analyse the behaviour of these achievable rates in the limit as the signal-to-noise ratio (SNR) tends to infinity. We demonstrate that nearest neighbour decoding and pilot-aided channel estimation achieves the capacity pre-log-which is defined as the limiting ratio of the capacity to the logarithm of SNR as the SNR tends to infinity-of non-coherent multiple-input single-output (MISO) flat-fading channels, and it achieves the best so far known lower bound on the capacity pre-log of non-coherent MIMO flat-fading channels.
Maiz, Cristina S; Miguez, Joaquin
On the Optimization of Transportation Routes with Multiple Destinations in Random Networks Artículo en actas
En: 2011 IEEE Statistical Signal Processing Workshop (SSP), pp. 349–352, IEEE, Nice, 2011, ISBN: 978-1-4577-0569-4.
Resumen | Enlaces | BibTeX | Etiquetas: Approximation algorithms, communication networks, Estimation, graph theory, Histograms, intelligent transportation, Monte Carlo algorithm, Monte Carlo methods, multiple destinations, optimisation, Optimization, random networks, route optimization, routing, Sequential Monte Carlo, Signal processing algorithms, stochastic graph, Stochastic processes, telecommunication network routing, time-varying graph, transportation routes
@inproceedings{Maiz2011,
title = {On the Optimization of Transportation Routes with Multiple Destinations in Random Networks},
author = {Cristina S Maiz and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5967701},
isbn = {978-1-4577-0569-4},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE Statistical Signal Processing Workshop (SSP)},
pages = {349--352},
publisher = {IEEE},
address = {Nice},
abstract = {Various practical problems in transportation research and routing in communication networks can be reduced to the computation of the best path that traverses a certain graph and visits a set of D specified destination nodes. Simple versions of this problem have received attention in the literature. Optimal solutions exist for the cases in which (a) D >; 1 and the graph is deterministic or (b) D = 1 and the graph is stochastic (and possibly time-dependent). Here, we address the general problem in which both D >; 1 and the costs of the edges in the graph are stochastic and time-varying. We tackle this complex global optimization problem by first converting it into an equivalent estimation problem and then computing a numerical solution using a sequential Monte Carlo algorithm. The advantage of the proposed technique over some standard methods (devised for graphs with time-invariant statistics) is illustrated by way of computer simulations.},
keywords = {Approximation algorithms, communication networks, Estimation, graph theory, Histograms, intelligent transportation, Monte Carlo algorithm, Monte Carlo methods, multiple destinations, optimisation, Optimization, random networks, route optimization, routing, Sequential Monte Carlo, Signal processing algorithms, stochastic graph, Stochastic processes, telecommunication network routing, time-varying graph, transportation routes},
pubstate = {published},
tppubtype = {inproceedings}
}
Various practical problems in transportation research and routing in communication networks can be reduced to the computation of the best path that traverses a certain graph and visits a set of D specified destination nodes. Simple versions of this problem have received attention in the literature. Optimal solutions exist for the cases in which (a) D >; 1 and the graph is deterministic or (b) D = 1 and the graph is stochastic (and possibly time-dependent). Here, we address the general problem in which both D >; 1 and the costs of the edges in the graph are stochastic and time-varying. We tackle this complex global optimization problem by first converting it into an equivalent estimation problem and then computing a numerical solution using a sequential Monte Carlo algorithm. The advantage of the proposed technique over some standard methods (devised for graphs with time-invariant statistics) is illustrated by way of computer simulations.
Salamanca, Luis; Olmos, Pablo M; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando
MAP Decoding for LDPC Codes over the Binary Erasure Channel Artículo en actas
En: 2011 IEEE Information Theory Workshop, pp. 145–149, IEEE, Paraty, 2011, ISBN: 978-1-4577-0437-6.
Resumen | Enlaces | BibTeX | Etiquetas: binary erasure channel, Channel Coding, computational complexity, Decoding, generalized peeling decoder, generalized tree-structured expectation propagatio, graphical models, Iterative decoding, LDPC codes, MAP decoding, MAP decoding algorithm, Maximum likelihood decoding, parity check codes, TEP decoder, tree graph theory, Tree graphs, tree-structured expectation propagation, trees (mathematics)
@inproceedings{Salamanca2011a,
title = {MAP Decoding for LDPC Codes over the Binary Erasure Channel},
author = {Luis Salamanca and Pablo M Olmos and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6089364},
isbn = {978-1-4577-0437-6},
year = {2011},
date = {2011-01-01},
booktitle = {2011 IEEE Information Theory Workshop},
pages = {145--149},
publisher = {IEEE},
address = {Paraty},
abstract = {In this paper, we propose a decoding algorithm for LDPC codes that achieves the MAP solution over the BEC. This algorithm, denoted as generalized tree-structured expectation propagation (GTEP), extends the idea of our previous work, the TEP decoder. The GTEP modifies the graph by eliminating a check node of any degree and merging this information with the remaining graph. The GTEP decoder upon completion either provides the unique MAP solution or a tree graph in which the number of parent nodes indicates the multiplicity of the MAP solution. This algorithm can be easily described for the BEC, and it can be cast as a generalized peeling decoder. The GTEP naturally optimizes the complexity of the decoder, by looking for checks nodes of minimum degree to be eliminated first.},
keywords = {binary erasure channel, Channel Coding, computational complexity, Decoding, generalized peeling decoder, generalized tree-structured expectation propagatio, graphical models, Iterative decoding, LDPC codes, MAP decoding, MAP decoding algorithm, Maximum likelihood decoding, parity check codes, TEP decoder, tree graph theory, Tree graphs, tree-structured expectation propagation, trees (mathematics)},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we propose a decoding algorithm for LDPC codes that achieves the MAP solution over the BEC. This algorithm, denoted as generalized tree-structured expectation propagation (GTEP), extends the idea of our previous work, the TEP decoder. The GTEP modifies the graph by eliminating a check node of any degree and merging this information with the remaining graph. The GTEP decoder upon completion either provides the unique MAP solution or a tree graph in which the number of parent nodes indicates the multiplicity of the MAP solution. This algorithm can be easily described for the BEC, and it can be cast as a generalized peeling decoder. The GTEP naturally optimizes the complexity of the decoder, by looking for checks nodes of minimum degree to be eliminated first.
Achutegui, Katrin; Miguez, Joaquin
A Parallel Resampling Scheme and its Application to Distributed Particle Filtering in Wireless Networks Artículo en actas
En: 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 81–84, IEEE, San Juan, 2011, ISBN: 978-1-4577-2105-2.
Resumen | Enlaces | BibTeX | Etiquetas: Approximation algorithms, Approximation methods, Artificial neural networks, distributed resampling, DRNA technique, Markov processes, nonproportional allocation algorithm, parallel resampling scheme, PF, quantization, Signal processing, Vectors, Wireless sensor network, Wireless Sensor Networks, WSN
@inproceedings{Achutegui2011,
title = {A Parallel Resampling Scheme and its Application to Distributed Particle Filtering in Wireless Networks},
author = {Katrin Achutegui and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=6136051},
isbn = {978-1-4577-2105-2},
year = {2011},
date = {2011-01-01},
booktitle = {2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},
pages = {81--84},
publisher = {IEEE},
address = {San Juan},
abstract = {We address the design of a particle filter (PF) that can be implemented in a distributed manner over a network of wireless sensor nodes, each of them collecting their own local data. This is a problem that has received considerable attention lately and several methods based on consensus, the transmission of likelihood information, the truncation and/or the quantization of data have been proposed. However, all existing schemes suffer from limitations related either to the amount of required communications among the nodes or the accuracy of the filter outputs. In this work we propose a novel distributed PF that is built around the distributed resampling with non-proportional allocation (DRNA) algorithm. This scheme guarantees the properness of the particle approximations produced by the filter and has been shown to be both efficient and accurate when compared with centralized PFs. The standard DRNA technique, however, places stringent demands on the communications among nodes that turn out impractical for a typical wireless sensor network (WSN). In this paper we investigate how to reduce this communication load by using (i) a random model for the spread of data over the WSN and (ii) methods that enable the out-of-sequence processing of sensor observations. A simple numerical illustration of the performance of the new algorithm compared with a centralized PF is provided.},
keywords = {Approximation algorithms, Approximation methods, Artificial neural networks, distributed resampling, DRNA technique, Markov processes, nonproportional allocation algorithm, parallel resampling scheme, PF, quantization, Signal processing, Vectors, Wireless sensor network, Wireless Sensor Networks, WSN},
pubstate = {published},
tppubtype = {inproceedings}
}
We address the design of a particle filter (PF) that can be implemented in a distributed manner over a network of wireless sensor nodes, each of them collecting their own local data. This is a problem that has received considerable attention lately and several methods based on consensus, the transmission of likelihood information, the truncation and/or the quantization of data have been proposed. However, all existing schemes suffer from limitations related either to the amount of required communications among the nodes or the accuracy of the filter outputs. In this work we propose a novel distributed PF that is built around the distributed resampling with non-proportional allocation (DRNA) algorithm. This scheme guarantees the properness of the particle approximations produced by the filter and has been shown to be both efficient and accurate when compared with centralized PFs. The standard DRNA technique, however, places stringent demands on the communications among nodes that turn out impractical for a typical wireless sensor network (WSN). In this paper we investigate how to reduce this communication load by using (i) a random model for the spread of data over the WSN and (ii) methods that enable the out-of-sequence processing of sensor observations. A simple numerical illustration of the performance of the new algorithm compared with a centralized PF is provided.
Asyhari, Taufiq A; Koch, Tobias; i Fabregas, Albert Guillen
Nearest Neighbour Decoding with Pilot-Assisted Channel Estimation for Fading Multiple-Access Channels Artículo en actas
En: 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp. 1686–1693, IEEE, Allerton, 2011, ISBN: 978-1-4577-1818-2.
Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, Decoding, Fading, fading channels, fading multiple-access channels, MIMO, MIMO communication, multi-access systems, multiple-input multiple-output channel, nearest-neighbour decoding, noncoherent MIMO fading MAC channel, pilot-assisted channel estimation, Receiving antennas, Signal to noise ratio, signal-to-noise ratio, Time division multiple access, Vectors
@inproceedings{Asyhari2011a,
title = {Nearest Neighbour Decoding with Pilot-Assisted Channel Estimation for Fading Multiple-Access Channels},
author = {Taufiq A Asyhari and Tobias Koch and Albert Guillen i Fabregas},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6120371},
isbn = {978-1-4577-1818-2},
year = {2011},
date = {2011-01-01},
booktitle = {2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton)},
pages = {1686--1693},
publisher = {IEEE},
address = {Allerton},
abstract = {This paper studies a noncoherent multiple-input multiple-output (MIMO) fading multiple-access channel (MAC). The rate region that is achievable with nearest neighbour decoding and pilot-assisted channel estimation is analysed and the corresponding pre-log region, defined as the limiting ratio of the rate region to the logarithm of the signal-to-noise ratio (SNR) as the SNR tends to infinity, is determined.},
keywords = {Channel estimation, Decoding, Fading, fading channels, fading multiple-access channels, MIMO, MIMO communication, multi-access systems, multiple-input multiple-output channel, nearest-neighbour decoding, noncoherent MIMO fading MAC channel, pilot-assisted channel estimation, Receiving antennas, Signal to noise ratio, signal-to-noise ratio, Time division multiple access, Vectors},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper studies a noncoherent multiple-input multiple-output (MIMO) fading multiple-access channel (MAC). The rate region that is achievable with nearest neighbour decoding and pilot-assisted channel estimation is analysed and the corresponding pre-log region, defined as the limiting ratio of the rate region to the logarithm of the signal-to-noise ratio (SNR) as the SNR tends to infinity, is determined.
Ruiz, Francisco J R; Perez-Cruz, Fernando
Zero-Error Codes for the Noisy-Typewriter Channel Artículo en actas
En: Summer Research Institute (SuRi), Lausanne, 2011.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Ruiz2011a,
title = {Zero-Error Codes for the Noisy-Typewriter Channel},
author = {Francisco J R Ruiz and Fernando Perez-Cruz},
url = {http://suri.epfl.ch/past/2011},
year = {2011},
date = {2011-01-01},
booktitle = {Summer Research Institute (SuRi)},
address = {Lausanne},
abstract = {In this paper we propose nontrivial codes that achieve a non-zero zero-error rate for several odd-letter noisy-typewriter channels. Some of these codes (specifically those which are defined for a number of letters of the channel of the form 2^n+1) achieve the best-known lower bound on the zero-error capacity. We build the codes using linear codes over rings as we do not require the multiplicative inverse to build the codes.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we propose nontrivial codes that achieve a non-zero zero-error rate for several odd-letter noisy-typewriter channels. Some of these codes (specifically those which are defined for a number of letters of the channel of the form 2^n+1) achieve the best-known lower bound on the zero-error capacity. We build the codes using linear codes over rings as we do not require the multiplicative inverse to build the codes.
Shan, Gong; Artés-Rodríguez, Antonio
Fast Background Elimination in Fluorescence Microbiology Images: Comparison of Four Algorithms Artículo en actas
En: 7th Artificial Intelligence Applications and Innovations Conference, pp. 285 – 290, Corfú, 2011.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Shan2011,
title = {Fast Background Elimination in Fluorescence Microbiology Images: Comparison of Four Algorithms},
author = {Gong Shan and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://link.springer.com/chapter/10.1007/978-3-642-23960-1_34},
year = {2011},
date = {2011-01-01},
booktitle = {7th Artificial Intelligence Applications and Innovations Conference},
pages = {285 -- 290},
address = {Corf\'{u}},
abstract = {In this work, we investigate a fast background elimination front-end of an automatic bacilli detection system. This background eliminating system consists of a feature descriptor followed by a linear-SVMs classifier. Four state-of-the-art feature extraction algorithms are analyzed and modified. Extensive experiments have been made on real sputum fluorescence images and the results reveal that 96.92% of the background content can be correctly removed from one image with an acceptable computational complexity.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this work, we investigate a fast background elimination front-end of an automatic bacilli detection system. This background eliminating system consists of a feature descriptor followed by a linear-SVMs classifier. Four state-of-the-art feature extraction algorithms are analyzed and modified. Extensive experiments have been made on real sputum fluorescence images and the results reveal that 96.92% of the background content can be correctly removed from one image with an acceptable computational complexity.
Koblents, Eugenia; Miguez, Joaquin
A Population Monte Carlo Method for Bayesian Inference and its Application to Stochastic Kinetic Models Artículo en actas
En: EUSIPCO 2011, Barcelona, 2011.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Koblents2011,
title = {A Population Monte Carlo Method for Bayesian Inference and its Application to Stochastic Kinetic Models},
author = {Eugenia Koblents and Joaquin Miguez},
url = {http://www.eurasip.org/Proceedings/Eusipco/Eusipco2011/papers/1569427761.pdf},
year = {2011},
date = {2011-01-01},
booktitle = {EUSIPCO 2011},
address = {Barcelona},
abstract = {We introduce an extension of the population Monte Carlo (PMC) methodology to address the problem of Bayesian in- ference in high dimensional models. Specifically, we intro- duce a technique for the selection and update of importance functions based on the construction of Gaussian Bayesian networks. The structure of the latter graphical model en- ables a sequential sampling procedure that requires draw- ing only from unidimensional conditional distributions an d leads to very efficient PMC algorithms. In order to illus- trate the potential of the new technique we have consid- ered the estimation of rate parameters in stochastic kineti c models (SKMs). SKMs are multivariate systems that model molecular interactions in biological and chemical problem s. We present some numerical results based on a simple SKM known as predator-prey mode},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We introduce an extension of the population Monte Carlo (PMC) methodology to address the problem of Bayesian in- ference in high dimensional models. Specifically, we intro- duce a technique for the selection and update of importance functions based on the construction of Gaussian Bayesian networks. The structure of the latter graphical model en- ables a sequential sampling procedure that requires draw- ing only from unidimensional conditional distributions an d leads to very efficient PMC algorithms. In order to illus- trate the potential of the new technique we have consid- ered the estimation of rate parameters in stochastic kineti c models (SKMs). SKMs are multivariate systems that model molecular interactions in biological and chemical problem s. We present some numerical results based on a simple SKM known as predator-prey mode
Vazquez, Manuel A; Miguez, Joaquin
A Per-Survivor Processing Receiver for MIMO Transmission Systems With One Unknown Channel Order Per Output Artículo de revista
En: IEEE Transactions on Vehicular Technology, vol. 60, no. 9, pp. 4415–4426, 2011, ISSN: 0018-9545.
Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, communication channel, Complexity theory, dynamic programming, frequency-selective MIMO channel, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channel impulse response coefficient, MIMO communication, MIMO transmission system, multipath channels, mutiple-input–multiple-output (MIMO), per-survivor processing receiver, Receiving antennas, Signal processing algorithms, time-selective MIMO channel, Transmitting antennas, Viterbi algorithm
@article{Vazquez2011,
title = {A Per-Survivor Processing Receiver for MIMO Transmission Systems With One Unknown Channel Order Per Output},
author = {Manuel A Vazquez and Joaquin Miguez},
url = {http://www.tsc.uc3m.es/~jmiguez/papers/P31_2011_A Per-Survivor Processing Receiver for MIMO Transmission Systems With One Unknown Channel Order Per Output.pdf http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6032763},
issn = {0018-9545},
year = {2011},
date = {2011-01-01},
journal = {IEEE Transactions on Vehicular Technology},
volume = {60},
number = {9},
pages = {4415--4426},
abstract = {The order of a communications channel is the length of its impulse response. Recently, several works have tackled the problem of estimating the order of a frequency-selective multiple-input-multiple-output (MIMO) channel. However, all of them consider a single order, despite the fact that a MIMO channel comprises several subchannels (specifically, as many as the number of inputs times the number of outputs), each one possibly with its own order. In this paper, we introduce an algorithm for maximum-likelihood sequence detection (MLSD) in frequency- and time-selective MIMO channels that incorporates full estimation of the MIMO channel impulse response (CIR) coefficients, including one channel order per output. Simulation results following the analytical derivation of the algorithm suggest that the proposed receiver can achieve significant improvements in performance when transmitting through a MIMO channel that effectively comprises subchannels of different lengths.},
keywords = {Channel estimation, communication channel, Complexity theory, dynamic programming, frequency-selective MIMO channel, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channel impulse response coefficient, MIMO communication, MIMO transmission system, multipath channels, mutiple-input\textendashmultiple-output (MIMO), per-survivor processing receiver, Receiving antennas, Signal processing algorithms, time-selective MIMO channel, Transmitting antennas, Viterbi algorithm},
pubstate = {published},
tppubtype = {article}
}
The order of a communications channel is the length of its impulse response. Recently, several works have tackled the problem of estimating the order of a frequency-selective multiple-input-multiple-output (MIMO) channel. However, all of them consider a single order, despite the fact that a MIMO channel comprises several subchannels (specifically, as many as the number of inputs times the number of outputs), each one possibly with its own order. In this paper, we introduce an algorithm for maximum-likelihood sequence detection (MLSD) in frequency- and time-selective MIMO channels that incorporates full estimation of the MIMO channel impulse response (CIR) coefficients, including one channel order per output. Simulation results following the analytical derivation of the algorithm suggest that the proposed receiver can achieve significant improvements in performance when transmitting through a MIMO channel that effectively comprises subchannels of different lengths.
Olmos, Pablo M; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando
Tree-Structured Expectation Propagation for Decoding Finite-Length LDPC Codes Artículo de revista
En: IEEE Communications Letters, vol. 15, no. 2, pp. 235–237, 2011, ISSN: 1089-7798.
Resumen | Enlaces | BibTeX | Etiquetas: belief propagation decoder, BP algorithm, BP decoder, code graph, communication complexity, computational complexity, Decoding, finite-length analysis, finite-length low-density parity-check code, LDPC code, LDPC decoding, parity check codes, radiowave propagation, stopping set, TEP algorithm, TEP decoder, tree-structured expectation propagation
@article{Olmos2011c,
title = {Tree-Structured Expectation Propagation for Decoding Finite-Length LDPC Codes},
author = {Pablo M Olmos and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5682215},
issn = {1089-7798},
year = {2011},
date = {2011-01-01},
journal = {IEEE Communications Letters},
volume = {15},
number = {2},
pages = {235--237},
abstract = {In this paper, we propose Tree-structured Expectation Propagation (TEP) algorithm to decode finite-length Low-Density Parity-Check (LDPC) codes. The TEP decoder is able to continue decoding once the standard Belief Propagation (BP) decoder fails, presenting the same computational complexity as the BP decoder. The BP algorithm is dominated by the presence of stopping sets (SSs) in the code graph. We show that the TEP decoder, without previous knowledge of the graph, naturally avoids some fairly common SSs. This results in a significant improvement in the system performance.},
keywords = {belief propagation decoder, BP algorithm, BP decoder, code graph, communication complexity, computational complexity, Decoding, finite-length analysis, finite-length low-density parity-check code, LDPC code, LDPC decoding, parity check codes, radiowave propagation, stopping set, TEP algorithm, TEP decoder, tree-structured expectation propagation},
pubstate = {published},
tppubtype = {article}
}
In this paper, we propose Tree-structured Expectation Propagation (TEP) algorithm to decode finite-length Low-Density Parity-Check (LDPC) codes. The TEP decoder is able to continue decoding once the standard Belief Propagation (BP) decoder fails, presenting the same computational complexity as the BP decoder. The BP algorithm is dominated by the presence of stopping sets (SSs) in the code graph. We show that the TEP decoder, without previous knowledge of the graph, naturally avoids some fairly common SSs. This results in a significant improvement in the system performance.
Asheghan, Mohammad Mostafa; Miguez, Joaquin; Hamidi-Beheshti, Mohammad Taghi; Tavazoei, Mohammad Saleh
Robust Outer Synchronization between two Complex Networks with Fractional Order Dynamics Artículo de revista
En: Chaos (Woodbury, N.Y.), vol. 21, no. 3, pp. 033121, 2011, ISSN: 1089-7682.
Resumen | Enlaces | BibTeX | Etiquetas:
@article{Asheghan2011,
title = {Robust Outer Synchronization between two Complex Networks with Fractional Order Dynamics},
author = {Mohammad Mostafa Asheghan and Joaquin Miguez and Mohammad Taghi Hamidi-Beheshti and Mohammad Saleh Tavazoei},
url = {http://www.tsc.uc3m.es/~jmiguez/papers/P32_2011_Robust Outer Synchronization between two Complex Networks with Fractional Order Dynamics.pdf
http://scitation.aip.org/content/aip/journal/chaos/21/3/10.1063/1.3629986},
issn = {1089-7682},
year = {2011},
date = {2011-01-01},
journal = {Chaos (Woodbury, N.Y.)},
volume = {21},
number = {3},
pages = {033121},
publisher = {AIP Publishing},
abstract = {Synchronization between two coupled complex networks with fractional-order dynamics, hereafter referred to as outer synchronization, is investigated in this work. In particular, we consider two systems consisting of interconnected nodes. The state variables of each node evolve with time according to a set of (possibly nonlinear and chaotic) fractional-order differential equations. One of the networks plays the role of a master system and drives the second network by way of an open-plus-closed-loop (OPCL) scheme. Starting from a simple analysis of the synchronization error and a basic lemma on the eigenvalues of matrices resulting from Kronecker products, we establish various sets of conditions for outer synchronization, i.e., for ensuring that the errors between the state variables of the master and response systems can asymptotically vanish with time. Then, we address the problem of robust outer synchronization, i.e., how to guarantee that the states of the nodes converge to common values when the parameters of the master and response networks are not identical, but present some perturbations. Assuming that these perturbations are bounded, we also find conditions for outer synchronization, this time given in terms of sets of linear matrix inequalities (LMIs). Most of the analytical results in this paper are valid both for fractional-order and integer-order dynamics. The assumptions on the inner (coupling) structure of the networks are mild, involving, at most, symmetry and diffusivity. The analytical results are complemented with numerical examples. In particular, we show examples of generalized and robust outer synchronization for networks whose nodes are governed by fractional-order Lorenz dynamics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Synchronization between two coupled complex networks with fractional-order dynamics, hereafter referred to as outer synchronization, is investigated in this work. In particular, we consider two systems consisting of interconnected nodes. The state variables of each node evolve with time according to a set of (possibly nonlinear and chaotic) fractional-order differential equations. One of the networks plays the role of a master system and drives the second network by way of an open-plus-closed-loop (OPCL) scheme. Starting from a simple analysis of the synchronization error and a basic lemma on the eigenvalues of matrices resulting from Kronecker products, we establish various sets of conditions for outer synchronization, i.e., for ensuring that the errors between the state variables of the master and response systems can asymptotically vanish with time. Then, we address the problem of robust outer synchronization, i.e., how to guarantee that the states of the nodes converge to common values when the parameters of the master and response networks are not identical, but present some perturbations. Assuming that these perturbations are bounded, we also find conditions for outer synchronization, this time given in terms of sets of linear matrix inequalities (LMIs). Most of the analytical results in this paper are valid both for fractional-order and integer-order dynamics. The assumptions on the inner (coupling) structure of the networks are mild, involving, at most, symmetry and diffusivity. The analytical results are complemented with numerical examples. In particular, we show examples of generalized and robust outer synchronization for networks whose nodes are governed by fractional-order Lorenz dynamics.
Delgado-Gómez, David; Aguado, David; Lopez-Castroman, Jorge; Santacruz, Carlos; Artés-Rodríguez, Antonio
Improving Sale Performance Prediction Using Support Vector Machines Artículo de revista
En: Expert Systems with Applications, vol. 38, no. 5, pp. 5129–5132, 2011.
Resumen | Enlaces | BibTeX | Etiquetas: Recruitment process, Sale performance prediction, Support vector machines
@article{Delgado-Gomez2011a,
title = {Improving Sale Performance Prediction Using Support Vector Machines},
author = {David Delgado-G\'{o}mez and David Aguado and Jorge Lopez-Castroman and Carlos Santacruz and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.tsc.uc3m.es/~antonio/papers/P41_2011_Improving Sale Performance Prediction Using Support Vector Machines.pdf
http://www.sciencedirect.com/science/article/pii/S0957417410011322},
year = {2011},
date = {2011-01-01},
journal = {Expert Systems with Applications},
volume = {38},
number = {5},
pages = {5129--5132},
abstract = {In this article, an expert system based on support vector machines is developed to predict the sale performance of some insurance company candidates. The system predicts the performance of these candidates based on some scores, which are measurements of cognitive characteristics, personality, selling skills and biodata. An experiment is conducted to compare the accuracy of the proposed system with respect to previously reported systems which use discriminant functions or decision trees. Results show that the proposed system is able to improve the accuracy of a baseline linear discriminant based system by more than 10% and that also exceeds the state of the art systems by almost 5%. The proposed approach can help to reduce considerably the direct and indirect expenses of the companies.},
keywords = {Recruitment process, Sale performance prediction, Support vector machines},
pubstate = {published},
tppubtype = {article}
}
In this article, an expert system based on support vector machines is developed to predict the sale performance of some insurance company candidates. The system predicts the performance of these candidates based on some scores, which are measurements of cognitive characteristics, personality, selling skills and biodata. An experiment is conducted to compare the accuracy of the proposed system with respect to previously reported systems which use discriminant functions or decision trees. Results show that the proposed system is able to improve the accuracy of a baseline linear discriminant based system by more than 10% and that also exceeds the state of the art systems by almost 5%. The proposed approach can help to reduce considerably the direct and indirect expenses of the companies.
Delgado-Gómez, David; Blasco-Fontecilla, Hilario; Alegria, AnaLucia A; Legido-Gil, Teresa; Artés-Rodríguez, Antonio; Baca-García, Enrique
Improving the Accuracy of Suicide Attempter Classification Artículo de revista
En: Artificial Intelligence in Medicine, vol. 52, no. 3, pp. 165–168, 2011.
Resumen | Enlaces | BibTeX | Etiquetas: Barratt’s impulsiveness scale, Boosting, International personality disorder evaluation scre, Suicide prediction, Support vector machines
@article{Delgado-Gomez2011b,
title = {Improving the Accuracy of Suicide Attempter Classification},
author = {David Delgado-G\'{o}mez and Hilario Blasco-Fontecilla and AnaLucia A Alegria and Teresa Legido-Gil and Antonio Art\'{e}s-Rodr\'{i}guez and Enrique Baca-Garc\'{i}a},
url = {http://www.sciencedirect.com/science/article/pii/S0933365711000595},
year = {2011},
date = {2011-01-01},
journal = {Artificial Intelligence in Medicine},
volume = {52},
number = {3},
pages = {165--168},
abstract = {OBJECTIVE Psychometrical questionnaires such as the Barrat’s impulsiveness scale version 11 (BIS-11) have been used in the assessment of suicidal behavior. Traditionally, BIS-11 items have been considered as equally valuable but this might not be true. The main objective of this article is to test the discriminative ability of the BIS-11 and the international personality disorder evaluation screening questionnaire (IPDE-SQ) to predict suicide attempter (SA) status using different classification techniques. In addition, we examine the discriminative capacity of individual items from both scales. MATERIALS AND METHODS Two experiments aimed at evaluating the accuracy of different classification techniques were conducted. The answers of 879 individuals (345 SA, 384 healthy blood donors, and 150 psychiatric inpatients) to the BIS-11 and IPDE-SQ were used to compare the classification performance of two techniques that have successfully been applied in pattern recognition issues, Boosting and support vector machines (SVM) with respect to linear discriminant analysis, Fisher linear discriminant analysis, and the traditional psychometrical approach. RESULTS The most discriminative BIS-11 and IPDE-SQ items are “I am self controlled” (Item 6) and “I often feel empty inside” (item 40), respectively. The SVM classification accuracy was 76.71% for the BIS-11 and 80.26% for the IPDE-SQ. CONCLUSIONS The IPDE-SQ items have better discriminative abilities than the BIS-11 items for classifying SA. Moreover, IPDE-SQ is able to obtain better SA and non-SA classification results than the BIS-11. In addition, SVM outperformed the other classification techniques in both questionnaires.},
keywords = {Barratt’s impulsiveness scale, Boosting, International personality disorder evaluation scre, Suicide prediction, Support vector machines},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE Psychometrical questionnaires such as the Barrat’s impulsiveness scale version 11 (BIS-11) have been used in the assessment of suicidal behavior. Traditionally, BIS-11 items have been considered as equally valuable but this might not be true. The main objective of this article is to test the discriminative ability of the BIS-11 and the international personality disorder evaluation screening questionnaire (IPDE-SQ) to predict suicide attempter (SA) status using different classification techniques. In addition, we examine the discriminative capacity of individual items from both scales. MATERIALS AND METHODS Two experiments aimed at evaluating the accuracy of different classification techniques were conducted. The answers of 879 individuals (345 SA, 384 healthy blood donors, and 150 psychiatric inpatients) to the BIS-11 and IPDE-SQ were used to compare the classification performance of two techniques that have successfully been applied in pattern recognition issues, Boosting and support vector machines (SVM) with respect to linear discriminant analysis, Fisher linear discriminant analysis, and the traditional psychometrical approach. RESULTS The most discriminative BIS-11 and IPDE-SQ items are “I am self controlled” (Item 6) and “I often feel empty inside” (item 40), respectively. The SVM classification accuracy was 76.71% for the BIS-11 and 80.26% for the IPDE-SQ. CONCLUSIONS The IPDE-SQ items have better discriminative abilities than the BIS-11 items for classifying SA. Moreover, IPDE-SQ is able to obtain better SA and non-SA classification results than the BIS-11. In addition, SVM outperformed the other classification techniques in both questionnaires.
Miguez, Joaquin; Crisan, Dan; Djuric, Petar M
On the Convergence of Two Sequential Monte Carlo Methods for Maximum a Posteriori Sequence Estimation and Stochastic Global Optimization Artículo de revista
En: Statistics and Computing, vol. 23, no. 1, pp. 91–107, 2011, ISSN: 0960-3174.
Resumen | Enlaces | BibTeX | Etiquetas: Global optimization, MAP sequence estimation, Sequential Monte Carlo, State space models
@article{Miguez2011,
title = {On the Convergence of Two Sequential Monte Carlo Methods for Maximum a Posteriori Sequence Estimation and Stochastic Global Optimization},
author = {Joaquin Miguez and Dan Crisan and Petar M Djuric},
url = {http://www.researchgate.net/publication/225447686_On_the_convergence_of_two_sequential_Monte_Carlo_methods_for_maximum_a_posteriori_sequence_estimation_and_stochastic_global_optimization},
issn = {0960-3174},
year = {2011},
date = {2011-01-01},
journal = {Statistics and Computing},
volume = {23},
number = {1},
pages = {91--107},
abstract = {This paper addresses the problem of maximum a posteriori (MAP) sequence estimation in general state-space models. We consider two algorithms based on the sequential Monte Carlo (SMC) methodology (also known as particle filtering). We prove that they produce approximations of the MAP estimator and that they converge almost surely. We also derive a lower bound for the number of particles that are needed to achieve a given approximation accuracy. In the last part of the paper, we investigate the application of particle filtering and MAP estimation to the global optimization of a class of (possibly non-convex and possibly non-differentiable) cost functions. In particular, we show how to convert the cost-minimization problem into one of MAP sequence estimation for a state-space model that is “matched” to the cost of interest. We provide examples that illustrate the application of the methodology as well as numerical results.},
keywords = {Global optimization, MAP sequence estimation, Sequential Monte Carlo, State space models},
pubstate = {published},
tppubtype = {article}
}
This paper addresses the problem of maximum a posteriori (MAP) sequence estimation in general state-space models. We consider two algorithms based on the sequential Monte Carlo (SMC) methodology (also known as particle filtering). We prove that they produce approximations of the MAP estimator and that they converge almost surely. We also derive a lower bound for the number of particles that are needed to achieve a given approximation accuracy. In the last part of the paper, we investigate the application of particle filtering and MAP estimation to the global optimization of a class of (possibly non-convex and possibly non-differentiable) cost functions. In particular, we show how to convert the cost-minimization problem into one of MAP sequence estimation for a state-space model that is “matched” to the cost of interest. We provide examples that illustrate the application of the methodology as well as numerical results.
Lopez-Castroman, Jorge; Perez-Rodriguez, Mercedes M; Jaussent, Isabelle; Alegria, AnaLucia A; Artés-Rodríguez, Antonio; Freed, Peter; Guillaume, Sébastien; Jollant, Fabrice; Leiva-Murillo, Jose M; Malafosse, Alain; Oquendo, Maria A; de Prado-Cumplido, Mario; Saiz-Ruiz, Jeronimo; Baca-García, Enrique; Courtet, Philippe
Distinguishing the Relevant Features of Frequent Suicide Attempters Artículo de revista
En: Journal of psychiatric research, vol. 45, no. 5, pp. 619–625, 2011, ISSN: 1879-1379.
Resumen | Enlaces | BibTeX | Etiquetas: Adult, Attempted, Attempted: psychology, Attempted: statistics & numerical data, Female, France, Humans, Interview, Male, Middle Aged, Prevalence, Probability, Psychiatric Status Rating Scales, Psychological, Risk Factors, ROC Curve, Spain, Suicide
@article{Lopez-Castroman2011,
title = {Distinguishing the Relevant Features of Frequent Suicide Attempters},
author = {Jorge Lopez-Castroman and Mercedes M Perez-Rodriguez and Isabelle Jaussent and AnaLucia A Alegria and Antonio Art\'{e}s-Rodr\'{i}guez and Peter Freed and S\'{e}bastien Guillaume and Fabrice Jollant and Jose M Leiva-Murillo and Alain Malafosse and Maria A Oquendo and Mario de Prado-Cumplido and Jeronimo Saiz-Ruiz and Enrique Baca-Garc\'{i}a and Philippe Courtet},
url = {http://www.tsc.uc3m.es/~antonio/papers/P39_2011_Distinguishing the Relevant Features of Frequent Suicide Attempters.pdf
http://www.ncbi.nlm.nih.gov/pubmed/21055768},
issn = {1879-1379},
year = {2011},
date = {2011-01-01},
journal = {Journal of psychiatric research},
volume = {45},
number = {5},
pages = {619--625},
abstract = {BACKGROUND: In spite of the high prevalence of suicide behaviours and the magnitude of the resultant burden, little is known about why individuals reattempt. We aim to investigate the relationships between clinical risk factors and the repetition of suicidal attempts. METHODS: 1349 suicide attempters were consecutively recruited in the Emergency Room (ER) of two academic hospitals in France and Spain. Patients were extensively assessed and demographic and clinical data obtained. Data mining was used to determine the minimal number of variables that blinded the rest in relation to the number of suicide attempts. Using this set, a probabilistic graph ranking relationships with the target variable was constructed. RESULTS: The most common diagnoses among suicide attempters were affective disorders, followed by anxiety disorders. Risk of frequent suicide attempt was highest among middle-aged subjects, and diminished progressively with advancing age of onset at first attempt. Anxiety disorders significantly increased the risk of presenting frequent suicide attempts. Pathway analysis also indicated that frequent suicide attempts were linked to greater odds for alcohol and substance abuse disorders and more intensive treatment. CONCLUSIONS: Novel statistical methods found several clinical features that were associated with a history of frequent suicide attempts. The identified pathways may promote new hypothesis-driven studies of suicide attempts and preventive strategies.},
keywords = {Adult, Attempted, Attempted: psychology, Attempted: statistics \& numerical data, Female, France, Humans, Interview, Male, Middle Aged, Prevalence, Probability, Psychiatric Status Rating Scales, Psychological, Risk Factors, ROC Curve, Spain, Suicide},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: In spite of the high prevalence of suicide behaviours and the magnitude of the resultant burden, little is known about why individuals reattempt. We aim to investigate the relationships between clinical risk factors and the repetition of suicidal attempts. METHODS: 1349 suicide attempters were consecutively recruited in the Emergency Room (ER) of two academic hospitals in France and Spain. Patients were extensively assessed and demographic and clinical data obtained. Data mining was used to determine the minimal number of variables that blinded the rest in relation to the number of suicide attempts. Using this set, a probabilistic graph ranking relationships with the target variable was constructed. RESULTS: The most common diagnoses among suicide attempters were affective disorders, followed by anxiety disorders. Risk of frequent suicide attempt was highest among middle-aged subjects, and diminished progressively with advancing age of onset at first attempt. Anxiety disorders significantly increased the risk of presenting frequent suicide attempts. Pathway analysis also indicated that frequent suicide attempts were linked to greater odds for alcohol and substance abuse disorders and more intensive treatment. CONCLUSIONS: Novel statistical methods found several clinical features that were associated with a history of frequent suicide attempts. The identified pathways may promote new hypothesis-driven studies of suicide attempts and preventive strategies.
Tuia, D; Verrelst, J; Alonso, L; Perez-Cruz, Fernando; Camps-Valls, Gustavo
Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation Artículo de revista
En: IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 4, pp. 804–808, 2011, ISSN: 1545-598X.
Resumen | Enlaces | BibTeX | Etiquetas: Biological system modeling, Biomedical imaging, Biophysical parameter estimation, chlorophyll content estimation, Estimation, fractional vegetation cover, geophysical image processing, hyperspectral compact high-resolution imaging spec, image resolution, leaf area index, model inversion, multioutput support vector regression method, nonparametric biophysical parameter estimation, Parameter estimation, regression, regression analysis, Remote sensing, remote sensing biophysical parameter estimation, remote sensing image, single-output support vector regression method, spectrometers, Support vector machines, support vector regression (SVR), Vegetation mapping
@article{Tuia2011,
title = {Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation},
author = {D Tuia and J Verrelst and L Alonso and Fernando Perez-Cruz and Gustavo Camps-Valls},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5735189},
issn = {1545-598X},
year = {2011},
date = {2011-01-01},
journal = {IEEE Geoscience and Remote Sensing Letters},
volume = {8},
number = {4},
pages = {804--808},
abstract = {This letter proposes a multioutput support vector regression (M-SVR) method for the simultaneous estimation of different biophysical parameters from remote sensing images. General retrieval problems require multioutput (and potentially nonlinear) regression methods. M-SVR extends the single-output SVR to multiple outputs maintaining the advantages of a sparse and compact solution by using an $epsilon$-insensitive cost function. The proposed M-SVR is evaluated in the estimation of chlorophyll content, leaf area index and fractional vegetation cover from a hyperspectral compact high-resolution imaging spectrometer images. The achieved improvement with respect to the single-output regression approach suggests that M-SVR can be considered a convenient alternative for nonparametric biophysical parameter estimation and model inversion.},
keywords = {Biological system modeling, Biomedical imaging, Biophysical parameter estimation, chlorophyll content estimation, Estimation, fractional vegetation cover, geophysical image processing, hyperspectral compact high-resolution imaging spec, image resolution, leaf area index, model inversion, multioutput support vector regression method, nonparametric biophysical parameter estimation, Parameter estimation, regression, regression analysis, Remote sensing, remote sensing biophysical parameter estimation, remote sensing image, single-output support vector regression method, spectrometers, Support vector machines, support vector regression (SVR), Vegetation mapping},
pubstate = {published},
tppubtype = {article}
}
This letter proposes a multioutput support vector regression (M-SVR) method for the simultaneous estimation of different biophysical parameters from remote sensing images. General retrieval problems require multioutput (and potentially nonlinear) regression methods. M-SVR extends the single-output SVR to multiple outputs maintaining the advantages of a sparse and compact solution by using an $epsilon$-insensitive cost function. The proposed M-SVR is evaluated in the estimation of chlorophyll content, leaf area index and fractional vegetation cover from a hyperspectral compact high-resolution imaging spectrometer images. The achieved improvement with respect to the single-output regression approach suggests that M-SVR can be considered a convenient alternative for nonparametric biophysical parameter estimation and model inversion.
Santiago-Mozos, Ricardo; Perez-Cruz, Fernando; Artés-Rodríguez, Antonio
Extended Input Space Support Vector Machine Artículo de revista
En: IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council, vol. 22, no. 1, pp. 158–163, 2011, ISSN: 1941-0093.
Resumen | Enlaces | BibTeX | Etiquetas: Algorithms, Artificial Intelligence, Automated, Automated: standards, Computer Simulation, Computer Simulation: standards, Neural Networks (Computer), Pattern recognition, Problem Solving, Software Design, Software Validation
@article{Santiago-Mozos2011,
title = {Extended Input Space Support Vector Machine},
author = {Ricardo Santiago-Mozos and Fernando Perez-Cruz and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.tsc.uc3m.es/~antonio/papers/P38_2011_Extended Input Space Support Vector Machine.pdf
http://www.ncbi.nlm.nih.gov/pubmed/21095866},
issn = {1941-0093},
year = {2011},
date = {2011-01-01},
journal = {IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council},
volume = {22},
number = {1},
pages = {158--163},
abstract = {In some applications, the probability of error of a given classifier is too high for its practical application, but we are allowed to gather more independent test samples from the same class to reduce the probability of error of the final decision. From the point of view of hypothesis testing, the solution is given by the Neyman-Pearson lemma. However, there is no equivalent result to the Neyman-Pearson lemma when the likelihoods are unknown, and we are given a training dataset. In this brief, we explore two alternatives. First, we combine the soft (probabilistic) outputs of a given classifier to produce a consensus labeling for K test samples. In the second approach, we build a new classifier that directly computes the label for K test samples. For this second approach, we need to define an extended input space training set and incorporate the known symmetries in the classifier. This latter approach gives more accurate results, as it only requires an accurate classification boundary, while the former needs an accurate posterior probability estimate for the whole input space. We illustrate our results with well-known databases.},
keywords = {Algorithms, Artificial Intelligence, Automated, Automated: standards, Computer Simulation, Computer Simulation: standards, Neural Networks (Computer), Pattern recognition, Problem Solving, Software Design, Software Validation},
pubstate = {published},
tppubtype = {article}
}
In some applications, the probability of error of a given classifier is too high for its practical application, but we are allowed to gather more independent test samples from the same class to reduce the probability of error of the final decision. From the point of view of hypothesis testing, the solution is given by the Neyman-Pearson lemma. However, there is no equivalent result to the Neyman-Pearson lemma when the likelihoods are unknown, and we are given a training dataset. In this brief, we explore two alternatives. First, we combine the soft (probabilistic) outputs of a given classifier to produce a consensus labeling for K test samples. In the second approach, we build a new classifier that directly computes the label for K test samples. For this second approach, we need to define an extended input space training set and incorporate the known symmetries in the classifier. This latter approach gives more accurate results, as it only requires an accurate classification boundary, while the former needs an accurate posterior probability estimate for the whole input space. We illustrate our results with well-known databases.
Plata-Chaves, Jorge; Lazaro, Marcelino
Closed-Form Error Exponent for the Neyman–Pearson Fusion of Dependent Local Decisions in a One-Dimensional Sensor Network Artículo de revista
En: IEEE Transactions on Signal Processing, vol. 59, no. 3, pp. 1239–1254, 2011, ISSN: 1053-587X.
Resumen | Enlaces | BibTeX | Etiquetas:
@article{Plata-Chaves2011b,
title = {Closed-Form Error Exponent for the Neyman\textendashPearson Fusion of Dependent Local Decisions in a One-Dimensional Sensor Network},
author = {Jorge Plata-Chaves and Marcelino Lazaro},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5654602},
issn = {1053-587X},
year = {2011},
date = {2011-01-01},
journal = {IEEE Transactions on Signal Processing},
volume = {59},
number = {3},
pages = {1239--1254},
abstract = {We consider a distributed detection system formed by a large number of local detectors and a data fusion center that performs a Neyman-Pearson fusion of the binary quantizations of the sensor observations. In the analyzed two-stage detection system the local decisions are taken with no kind of cooperation among the devices and they are transmitted to the fusion center over an error free parallel access channel. In addition, the sensors are randomly deployed along a straight line, and the corresponding sensor spacings are drawn independently from a common probability density function (pdf). For both hypothesis, H0 and H1, depending on the correlation structure of the observed phenomenon the local decisions might be dependent. In the case of being dependent, their correlation structure is modelled with a one-dimensional Markov random field with nearest neighbor dependency and binary state space. Under this scenario, we first derive a closed-form error exponent for the Neyman-Pearson fusion of the local decisions when the involved data fusion center only knows the distribution of the sensor spacings. Second, based on a single parameter that captures the mean correlation strength among the local decisions, some analytical properties of the error exponent are investigated. Finally, we develop a physical model for the conditional probabilities of the Markov random fields that might be present under each hypothesis. Using this model we characterize the error exponent for two well-known models of the sensor spacing: i) equispaced sensors with failures, and ii) exponentially spaced sensors with failures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We consider a distributed detection system formed by a large number of local detectors and a data fusion center that performs a Neyman-Pearson fusion of the binary quantizations of the sensor observations. In the analyzed two-stage detection system the local decisions are taken with no kind of cooperation among the devices and they are transmitted to the fusion center over an error free parallel access channel. In addition, the sensors are randomly deployed along a straight line, and the corresponding sensor spacings are drawn independently from a common probability density function (pdf). For both hypothesis, H0 and H1, depending on the correlation structure of the observed phenomenon the local decisions might be dependent. In the case of being dependent, their correlation structure is modelled with a one-dimensional Markov random field with nearest neighbor dependency and binary state space. Under this scenario, we first derive a closed-form error exponent for the Neyman-Pearson fusion of the local decisions when the involved data fusion center only knows the distribution of the sensor spacings. Second, based on a single parameter that captures the mean correlation strength among the local decisions, some analytical properties of the error exponent are investigated. Finally, we develop a physical model for the conditional probabilities of the Markov random fields that might be present under each hypothesis. Using this model we characterize the error exponent for two well-known models of the sensor spacing: i) equispaced sensors with failures, and ii) exponentially spaced sensors with failures.
Barbosa, J L; Luengo, David
Distributed Target Detection in Centralized Wireless Sensor Networks with Communication Constraints Artículo en actas
En: 19th European Signal Processing Conference (EUSIPCO), Barcelona, 2011.
BibTeX | Etiquetas:
@inproceedings{Barbosa2011,
title = {Distributed Target Detection in Centralized Wireless Sensor Networks with Communication Constraints},
author = {J L Barbosa and David Luengo},
year = {2011},
date = {2011-01-01},
booktitle = {19th European Signal Processing Conference (EUSIPCO)},
address = {Barcelona},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Crisan, Dan; Miguez, Joaquin
Particle Aproximation of the Filtering Density and Its Derivates in General State. Space Models Artículo en actas
En: Bayesian Inference and Stochastic Processes (BISP 7), Getafe, 2011.
BibTeX | Etiquetas:
@inproceedings{Crisan2011,
title = {Particle Aproximation of the Filtering Density and Its Derivates in General State. Space Models},
author = {Dan Crisan and Joaquin Miguez},
year = {2011},
date = {2011-01-01},
booktitle = {Bayesian Inference and Stochastic Processes (BISP 7)},
address = {Getafe},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Plata-Chaves, Jorge; Lazaro, Marcelino; Artés-Rodríguez, Antonio
Optimal Neyman-Pearson Fusion in Two-Dimensional Densor Networks with Serial Architecture and Dependent Observations Artículo en actas
En: Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on, pp. 1–6, Chicago, 2011, ISBN: 978-1-4577-0267-9.
Resumen | Enlaces | BibTeX | Etiquetas: Bayesian methods, binary distributed detection problem, decision theory, dependent observations, Joints, local decision rule, Measurement uncertainty, Network topology, Neyman-Pearson criterion, optimal Neyman-Pearson fusion, optimum distributed detection, Parallel architectures, Performance evaluation, Probability density function, sensor dependent observations, sensor fusion, serial architecture, serial network topology, two-dimensional sensor networks, Wireless Sensor Networks
@inproceedings{Plata-Chaves2011bb,
title = {Optimal Neyman-Pearson Fusion in Two-Dimensional Densor Networks with Serial Architecture and Dependent Observations},
author = {Jorge Plata-Chaves and Marcelino Lazaro and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5977545\&searchWithin%3Dartes+rodriguez%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A5977431%29},
isbn = {978-1-4577-0267-9},
year = {2011},
date = {2011-01-01},
booktitle = {Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on},
pages = {1--6},
address = {Chicago},
abstract = {In this correspondence, we consider a sensor network with serial architecture. When solving a binary distributed detection problem where the sensor observations are dependent under each one of the two possible hypothesis, each fusion stage of the network applies a local decision rule. We assume that, based on the information available at each fusion stage, the decision rules provide a binary message regarding the presence or absence of an event of interest. Under this scenario and under a Neyman-Pearson formulation, we derive the optimal decision rules associated with each fusion stage. As it happens when the sensor observations are independent, we are able to show that, under the Neyman-Pearson criterion, the optimal fusion rules of a serial configuration with dependent observations also match optimal Neyman-Pearson tests.},
keywords = {Bayesian methods, binary distributed detection problem, decision theory, dependent observations, Joints, local decision rule, Measurement uncertainty, Network topology, Neyman-Pearson criterion, optimal Neyman-Pearson fusion, optimum distributed detection, Parallel architectures, Performance evaluation, Probability density function, sensor dependent observations, sensor fusion, serial architecture, serial network topology, two-dimensional sensor networks, Wireless Sensor Networks},
pubstate = {published},
tppubtype = {inproceedings}
}
In this correspondence, we consider a sensor network with serial architecture. When solving a binary distributed detection problem where the sensor observations are dependent under each one of the two possible hypothesis, each fusion stage of the network applies a local decision rule. We assume that, based on the information available at each fusion stage, the decision rules provide a binary message regarding the presence or absence of an event of interest. Under this scenario and under a Neyman-Pearson formulation, we derive the optimal decision rules associated with each fusion stage. As it happens when the sensor observations are independent, we are able to show that, under the Neyman-Pearson criterion, the optimal fusion rules of a serial configuration with dependent observations also match optimal Neyman-Pearson tests.
2010
Vazquez-Vilar, Gonzalo; Mosquera, Carlos; Jayaweera, Sudharman K
Primary User Enters the Game: Performance of Dynamic Spectrum Leasing in Cognitive Radio Networks Artículo de revista
En: IEEE Transactions on Wireless Communications, vol. 9, no. 12, pp. 3625-3629, 2010, ISSN: 1536-1276.
@article{twc2010,
title = {Primary User Enters the Game: Performance of Dynamic Spectrum Leasing in Cognitive Radio Networks},
author = {Gonzalo Vazquez-Vilar and Carlos Mosquera and Sudharman K Jayaweera},
doi = {10.1109/TWC.2010.101310.101056},
issn = {1536-1276},
year = {2010},
date = {2010-12-01},
journal = {IEEE Transactions on Wireless Communications},
volume = {9},
number = {12},
pages = {3625-3629},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
López-Valcarce, Roberto; Vazquez-Vilar, Gonzalo; Sala, Josep
Multiantenna spectrum sensing for Cognitive Radio: overcoming noise uncertainty Artículo en actas
En: The 2nd International Workshop on Cognitive Information Processing (CIP 2010), Elba Island (Tuscany), Italy, 2010, (Invited).
BibTeX | Etiquetas:
@inproceedings{cip2010,
title = {Multiantenna spectrum sensing for Cognitive Radio: overcoming noise uncertainty},
author = {Roberto L\'{o}pez-Valcarce and Gonzalo Vazquez-Vilar and Josep Sala},
year = {2010},
date = {2010-06-01},
booktitle = {The 2nd International Workshop on Cognitive Information Processing (CIP 2010)},
address = {Elba Island (Tuscany), Italy},
note = {Invited},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Jayaweera, Sudharman K; Vazquez-Vilar, Gonzalo; Mosquera, Carlos
Dynamic Spectrum Leasing (DSL): A New Paradigm for Spectrum Sharing in Cognitive Radio Networks Artículo de revista
En: IEEE Transactions on Vehicular Technology, vol. 59, no. 5, pp. 2328-2339, 2010, ISSN: 0018-9545.
@article{tvt2010,
title = {Dynamic Spectrum Leasing (DSL): A New Paradigm for Spectrum Sharing in Cognitive Radio Networks},
author = {Sudharman K Jayaweera and Gonzalo Vazquez-Vilar and Carlos Mosquera},
doi = {10.1109/TVT.2010.2042741},
issn = {0018-9545},
year = {2010},
date = {2010-06-01},
journal = {IEEE Transactions on Vehicular Technology},
volume = {59},
number = {5},
pages = {2328-2339},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
El-Howayek, Georges; Jayaweera, Sudharman K; Hakim, Kamrul; Vazquez-Vilar, Gonzalo; Mosquera, Carlos
Dynamic Spectrum Leasing (DSL) in Dynamic Channels Artículo en actas
En: ICC'10 Workshop on Cognitive Radio Interfaces and Signal Processing (ICC'10 Workshop CRISP), Cape Town, South Africa, 2010.
BibTeX | Etiquetas:
@inproceedings{crisp2010,
title = {Dynamic Spectrum Leasing (DSL) in Dynamic Channels},
author = {Georges El-Howayek and Sudharman K Jayaweera and Kamrul Hakim and Gonzalo Vazquez-Vilar and Carlos Mosquera},
year = {2010},
date = {2010-05-01},
booktitle = {ICC'10 Workshop on Cognitive Radio Interfaces and Signal Processing (ICC'10 Workshop CRISP)},
address = {Cape Town, South Africa},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Vazquez-Vilar, Gonzalo; López-Valcarce, Roberto; Mosquera, Carlos; González-Prelcic, Nuria
Wideband Spectral Estimation from Compressed Measurements Exploiting Spectral a priori Information in Cognitive Radio Systems Artículo en actas
En: 2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), Dallas, U.S.A., 2010.
BibTeX | Etiquetas:
@inproceedings{icassp2010,
title = {Wideband Spectral Estimation from Compressed Measurements Exploiting Spectral a priori Information in Cognitive Radio Systems},
author = {Gonzalo Vazquez-Vilar and Roberto L\'{o}pez-Valcarce and Carlos Mosquera and Nuria Gonz\'{a}lez-Prelcic},
year = {2010},
date = {2010-03-01},
booktitle = {2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)},
address = {Dallas, U.S.A.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Vazquez, Manuel A; Miguez, Joaquin
Adaptive MLSD for MIMO Transmission Systems with Unknown Subchannel Orders Artículo en actas
En: 2010 7th International Symposium on Wireless Communication Systems, pp. 451–455, IEEE, York, 2010, ISSN: 2154-0217.
Resumen | Enlaces | BibTeX | Etiquetas: Bit error rate, Channel estimation, channel impulse response, computational complexity, Estimation, frequency-selective multiple-input multiple-output, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO communication, MIMO transmission systems, multiple subchannels, per survivor processing methodology, pilot data, Receivers, Signal to noise ratio, Time frequency analysis, time selective MIMO channel
@inproceedings{Vazquez2010,
title = {Adaptive MLSD for MIMO Transmission Systems with Unknown Subchannel Orders},
author = {Manuel A Vazquez and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5624335},
issn = {2154-0217},
year = {2010},
date = {2010-01-01},
booktitle = {2010 7th International Symposium on Wireless Communication Systems},
pages = {451--455},
publisher = {IEEE},
address = {York},
abstract = {In the equalization of frequency-selective multiple-input multiple-output (MIMO) channels it is usually assumed that the length of the channel impulse response (CIR), also referred to as the channel order, is known. However, this is not true in most practical situations and, in order to avoid the serious performance degradation that occurs when the CIR length is underestimated, a channel with "more than enough" taps is usually considered. This very frequently leads to overestimating the channel order, which increases the computational complexity of any maximum likelihood sequence detection (MLSD) algorithm, while degrading its performance at the same time. The problem of estimating a single channel order for a time and frequency selective MIMO channel has recently been tackled. However, this is an idealized approach, since a MIMO channel comprises multiple subchannels (as many as the number of inputs times that of the outputs), each of them possibly with its own order. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including one channel order per output. The proposed technique is based on the per survivor processing (PSP) methodology, it admits both blind and semiblind implementations, depending on the availability of pilot data, and it is designed to work with time-selective channels. Besides the analytical derivation of the algorithm, we provide computer simulation results that illustrate the effectiveness of the resulting receiver.},
keywords = {Bit error rate, Channel estimation, channel impulse response, computational complexity, Estimation, frequency-selective multiple-input multiple-output, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO communication, MIMO transmission systems, multiple subchannels, per survivor processing methodology, pilot data, Receivers, Signal to noise ratio, Time frequency analysis, time selective MIMO channel},
pubstate = {published},
tppubtype = {inproceedings}
}
In the equalization of frequency-selective multiple-input multiple-output (MIMO) channels it is usually assumed that the length of the channel impulse response (CIR), also referred to as the channel order, is known. However, this is not true in most practical situations and, in order to avoid the serious performance degradation that occurs when the CIR length is underestimated, a channel with "more than enough" taps is usually considered. This very frequently leads to overestimating the channel order, which increases the computational complexity of any maximum likelihood sequence detection (MLSD) algorithm, while degrading its performance at the same time. The problem of estimating a single channel order for a time and frequency selective MIMO channel has recently been tackled. However, this is an idealized approach, since a MIMO channel comprises multiple subchannels (as many as the number of inputs times that of the outputs), each of them possibly with its own order. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including one channel order per output. The proposed technique is based on the per survivor processing (PSP) methodology, it admits both blind and semiblind implementations, depending on the availability of pilot data, and it is designed to work with time-selective channels. Besides the analytical derivation of the algorithm, we provide computer simulation results that illustrate the effectiveness of the resulting receiver.
Valera, Isabel; Sieskul, B T; Zheng, F; Kaiser, T
A Hybrid SS-ToA Wireless Ge- olocation Based on Path Attenuation under Imperfect Path Loss Exponent Artículo en actas
En: 18th European Signal Processing Conference (EUSIPCO-2010), Aalborg, 2010.
Resumen | Enlaces | BibTeX | Etiquetas: hood estimator, maximum likeli-, Path loss exponent, Time-of-arrival estimation
@inproceedings{Valera2010,
title = {A Hybrid SS-ToA Wireless Ge- olocation Based on Path Attenuation under Imperfect Path Loss Exponent},
author = {Isabel Valera and B T Sieskul and F Zheng and T Kaiser},
url = {http://www.eurasip.org/Proceedings/Eusipco/Eusipco2010/Contents/papers/1569292415.pdf},
year = {2010},
date = {2010-01-01},
booktitle = {18th European Signal Processing Conference (EUSIPCO-2010)},
address = {Aalborg},
abstract = {We consider the wireless geolocationusing the time of arrival (ToA) of radio signals in a cellular setting. The main concern in this paper involves the effects of the error knowledge of the path loss exponent (PLE). We derive the asymptotic error performance of the maximum likelihood (ML) estimator un- der the imperfect PLE. We point out that a previous method provides inaccurate performance prediction and then present a new method based on the Taylor series expansion. Numer- ical examples illustrate that the Taylor analysis captures the bias and the error variance of the ML estimator under the im- perfect PLE better than the conventional method. Simulation results also illustrate that in the threshold region, the ML es- timator outperforms the MC estimator even in the presence of the PLE error. However, in the asymptotic region the MC estimator and the ML estimator with the perfect PLE outper- form the ML estimator under the imperfect PLE.},
keywords = {hood estimator, maximum likeli-, Path loss exponent, Time-of-arrival estimation},
pubstate = {published},
tppubtype = {inproceedings}
}
We consider the wireless geolocationusing the time of arrival (ToA) of radio signals in a cellular setting. The main concern in this paper involves the effects of the error knowledge of the path loss exponent (PLE). We derive the asymptotic error performance of the maximum likelihood (ML) estimator un- der the imperfect PLE. We point out that a previous method provides inaccurate performance prediction and then present a new method based on the Taylor series expansion. Numer- ical examples illustrate that the Taylor analysis captures the bias and the error variance of the ML estimator under the im- perfect PLE better than the conventional method. Simulation results also illustrate that in the threshold region, the ML es- timator outperforms the MC estimator even in the presence of the PLE error. However, in the asymptotic region the MC estimator and the ML estimator with the perfect PLE outper- form the ML estimator under the imperfect PLE.
Martino, Luca; Miguez, Joaquin
A Rejection Sampling Scheme for Posterior Probability Distributions via the Ratio-of-Uniforms Method Artículo en actas
En: 18th European Signal Processing Conference (EUSIPCO-2010), Aalborg, 2010.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Martino2010,
title = {A Rejection Sampling Scheme for Posterior Probability Distributions via the Ratio-of-Uniforms Method},
author = {Luca Martino and Joaquin Miguez},
url = {http://www.academia.edu/2355638/A_rejection_sampling_scheme_for_posterior_probability_distributions_via_the_ratio-of-uniforms_method},
year = {2010},
date = {2010-01-01},
booktitle = {18th European Signal Processing Conference (EUSIPCO-2010)},
address = {Aalborg},
abstract = {Accept/reject sampling is a well-known method to generaterandom samples from arbitrary target probability distribu-tions. It demands the design of a suitable proposal probabil-ity density function (pdf) from which candidate samples canbe drawn. The main limitation to the use of RS is the needto find an adequate upper bound for the ratio of the targetpdf over the proposal pdf from which the samples are gener-ated. There are no general methods to analytically find thisbound, except when the target pdf is log-concave. In thispaper we introduce a novel procedure using the ratio of uni-forms method to efficiently perform rejection sampling fora large class of target densities. The candidate samples aregenerated using only two independent uniform random vari-ables. In order to illustrate the application of the proposedtechnique, we provide a numerical example},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Accept/reject sampling is a well-known method to generaterandom samples from arbitrary target probability distribu-tions. It demands the design of a suitable proposal probabil-ity density function (pdf) from which candidate samples canbe drawn. The main limitation to the use of RS is the needto find an adequate upper bound for the ratio of the targetpdf over the proposal pdf from which the samples are gener-ated. There are no general methods to analytically find thisbound, except when the target pdf is log-concave. In thispaper we introduce a novel procedure using the ratio of uni-forms method to efficiently perform rejection sampling fora large class of target densities. The candidate samples aregenerated using only two independent uniform random vari-ables. In order to illustrate the application of the proposedtechnique, we provide a numerical example
Ruiz, Manuel Martinez; Artés-Rodríguez, Antonio; Diaz-Rico, Jose Antonio; Fuentes, Jose Blanco
New Initiatives for Imagery Transmission over a Tactical Data Link. A Case Study: JPEG2000 Compressed Images Transmitted in a Link-16 Network. Method and Results Artículo en actas
En: 2010 - MILCOM 2010 MILITARY COMMUNICATIONS CONFERENCE, pp. 1163–1168, IEEE, San Jose, 2010, ISSN: 2155-7578.
Resumen | Enlaces | BibTeX | Etiquetas: Bit rate, code stream, data stream, Decoding, discrete wavelet transforms, Image coding, image compression, imagery transmission, JPEG-2000, JPEG2000 compressed images, link-16, Link-16 Enhance Throughput, Link-16 tactical network, MIDS-LVT, military communication, multirresolution, operational requirement, packing limit, PSNR, Security, Streaming media, tactical data link, time slot, Transform coding, wavelet discrete transforms, wavelets
@inproceedings{Martinez-Ruiz2010,
title = {New Initiatives for Imagery Transmission over a Tactical Data Link. A Case Study: JPEG2000 Compressed Images Transmitted in a Link-16 Network. Method and Results},
author = {Manuel Martinez Ruiz and Antonio Art\'{e}s-Rodr\'{i}guez and Jose Antonio Diaz-Rico and Jose Blanco Fuentes},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5680102},
issn = {2155-7578},
year = {2010},
date = {2010-01-01},
booktitle = {2010 - MILCOM 2010 MILITARY COMMUNICATIONS CONFERENCE},
pages = {1163--1168},
publisher = {IEEE},
address = {San Jose},
abstract = {This paper presents the results of an initiative to transmit imagery content through a Link-16 tactical network using a multirresolution approach based on wavelets to compress images. Firstly, we identify the operational requirements. Secondly, we justify why JPEG2000 is our choice for coding still images. Thirdly, we propose a method to map the JPEG2000 code-stream into Link-16 free-text messages. We propose to send the most important part of the JPEG2000 compressed image in a more error resistant Link-16 packed structure and the remaining of the image in less robust data structures but at higher data rates. Finally, we present our results based on software simulations and laboratory tests with real Link-16 terminals including a comparative analysis with Link-16 enhance throughput. A configuration using two MIDS-LVTs has being set up, along with JPEG2000 coding and decoding software tools.},
keywords = {Bit rate, code stream, data stream, Decoding, discrete wavelet transforms, Image coding, image compression, imagery transmission, JPEG-2000, JPEG2000 compressed images, link-16, Link-16 Enhance Throughput, Link-16 tactical network, MIDS-LVT, military communication, multirresolution, operational requirement, packing limit, PSNR, Security, Streaming media, tactical data link, time slot, Transform coding, wavelet discrete transforms, wavelets},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents the results of an initiative to transmit imagery content through a Link-16 tactical network using a multirresolution approach based on wavelets to compress images. Firstly, we identify the operational requirements. Secondly, we justify why JPEG2000 is our choice for coding still images. Thirdly, we propose a method to map the JPEG2000 code-stream into Link-16 free-text messages. We propose to send the most important part of the JPEG2000 compressed image in a more error resistant Link-16 packed structure and the remaining of the image in less robust data structures but at higher data rates. Finally, we present our results based on software simulations and laboratory tests with real Link-16 terminals including a comparative analysis with Link-16 enhance throughput. A configuration using two MIDS-LVTs has being set up, along with JPEG2000 coding and decoding software tools.
Koch, Tobias; Lapidoth, Amos
Increased Capacity per Unit-Cost by Oversampling Artículo en actas
En: 2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel, pp. 000684–000688, IEEE, Eliat, 2010, ISBN: 978-1-4244-8681-6.
Resumen | Enlaces | BibTeX | Etiquetas: AWGN, AWGN channels, bandlimited Gaussian channel, channel capacity, Gaussian channels, increased capacity per unit cost, Information rates, one bit output quantizer, oversampling, quantisation (signal), quantization, sampling rate recovery, signal sampling
@inproceedings{Koch2010,
title = {Increased Capacity per Unit-Cost by Oversampling},
author = {Tobias Koch and Amos Lapidoth},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5662127},
isbn = {978-1-4244-8681-6},
year = {2010},
date = {2010-01-01},
booktitle = {2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel},
pages = {000684--000688},
publisher = {IEEE},
address = {Eliat},
abstract = {It is demonstrated that doubling the sampling rate recovers some of the loss in capacity incurred on the bandlimited Gaussian channel with a one-bit output quantizer.},
keywords = {AWGN, AWGN channels, bandlimited Gaussian channel, channel capacity, Gaussian channels, increased capacity per unit cost, Information rates, one bit output quantizer, oversampling, quantisation (signal), quantization, sampling rate recovery, signal sampling},
pubstate = {published},
tppubtype = {inproceedings}
}
It is demonstrated that doubling the sampling rate recovers some of the loss in capacity incurred on the bandlimited Gaussian channel with a one-bit output quantizer.
Murillo-Fuentes, Juan Jose; Olmos, Pablo M; Perez-Cruz, Fernando
Analyzing the Maxwell Decoder for LDPC Codes in Binary Erasure Channels Artículo en actas
En: Information Theory and Applications (ITA), San Diego, 2010.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Murillo-Fuentes2010,
title = {Analyzing the Maxwell Decoder for LDPC Codes in Binary Erasure Channels},
author = {Juan Jose Murillo-Fuentes and Pablo M Olmos and Fernando Perez-Cruz},
url = {http://ita.ucsd.edu/workshop/10/files/abstract/abstract_1462.txt},
year = {2010},
date = {2010-01-01},
booktitle = {Information Theory and Applications (ITA)},
address = {San Diego},
abstract = {The Maxwell decoder has been proposed for bridging the gap between the achievable capacity by belief propagation decoding and the maximum a posteriori decoder in binary erasure channels of LDPC codes. The Maxwell decoder, once the belief-propagation decoder gets stuck in a nonempty stopping set, guesses a bit and replicates any running copies of the decoding process. Density evolution and EXIT chart analyses of this iterative decoder show that MAP performance can be derived from the performance of the BP decoder. The complexity of the Maxwell decoder depends exponentially on the number of guesses and a priori we cannot bound the number of guesses, which limits its applicability as a LDPC decoder. In this paper, we adapt the expectation propagation algorithm for LDPC decoding. Our algorithm can be understood as a Maxwell decoder with a bounded complexity. For unbounded complexity it achieves maximum a posteriori decoding. In this paper, we analyze in detail the simplest version of the algorithm, whose complexity is identical to belief propagation, and we demonstrate that the achieved capacity is higher than that of the belief propagation decoder.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The Maxwell decoder has been proposed for bridging the gap between the achievable capacity by belief propagation decoding and the maximum a posteriori decoder in binary erasure channels of LDPC codes. The Maxwell decoder, once the belief-propagation decoder gets stuck in a nonempty stopping set, guesses a bit and replicates any running copies of the decoding process. Density evolution and EXIT chart analyses of this iterative decoder show that MAP performance can be derived from the performance of the BP decoder. The complexity of the Maxwell decoder depends exponentially on the number of guesses and a priori we cannot bound the number of guesses, which limits its applicability as a LDPC decoder. In this paper, we adapt the expectation propagation algorithm for LDPC decoding. Our algorithm can be understood as a Maxwell decoder with a bounded complexity. For unbounded complexity it achieves maximum a posteriori decoding. In this paper, we analyze in detail the simplest version of the algorithm, whose complexity is identical to belief propagation, and we demonstrate that the achieved capacity is higher than that of the belief propagation decoder.
Olmos, Pablo M; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando
Tree-Structure Expectation Propagation for Decoding LDPC Codes over Binary Erasure Channels Artículo en actas
En: 2010 IEEE International Symposium on Information Theory, pp. 799–803, IEEE, Austin, TX, 2010, ISBN: 978-1-4244-7892-7.
Resumen | Enlaces | BibTeX | Etiquetas: belief propagation, binary erasure channels, Bipartite graph, BP decoder, Capacity planning, Channel Coding, codeword, computational complexity, Decoding, Finishing, graph theory, H infinity control, LDPC code decoding, LDPC Tanner graph, Maxwell decoder, parity check codes, Performance analysis, tree structure expectation propagation, trees (mathematics), Upper bound
@inproceedings{Olmos2010,
title = {Tree-Structure Expectation Propagation for Decoding LDPC Codes over Binary Erasure Channels},
author = {Pablo M Olmos and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5513636},
isbn = {978-1-4244-7892-7},
year = {2010},
date = {2010-01-01},
booktitle = {2010 IEEE International Symposium on Information Theory},
pages = {799--803},
publisher = {IEEE},
address = {Austin, TX},
abstract = {Expectation Propagation is a generalization to Belief Propagation (BP) in two ways. First, it can be used with any exponential family distribution over the cliques in the graph. Second, it can impose additional constraints on the marginal distributions. We use this second property to impose pair-wise marginal distribution constraints in some check nodes of the LDPC Tanner graph. These additional constraints allow decoding the received codeword when the BP decoder gets stuck. In this paper, we first present the new decoding algorithm, whose complexity is identical to the BP decoder, and we then prove that it is able to decode codewords with a larger fraction of erasures, as the block size tends to infinity. The proposed algorithm can be also understood as a simplification of the Maxwell decoder, but without its computational complexity. We also illustrate that the new algorithm outperforms the BP decoder for finite block-size codes.},
keywords = {belief propagation, binary erasure channels, Bipartite graph, BP decoder, Capacity planning, Channel Coding, codeword, computational complexity, Decoding, Finishing, graph theory, H infinity control, LDPC code decoding, LDPC Tanner graph, Maxwell decoder, parity check codes, Performance analysis, tree structure expectation propagation, trees (mathematics), Upper bound},
pubstate = {published},
tppubtype = {inproceedings}
}
Expectation Propagation is a generalization to Belief Propagation (BP) in two ways. First, it can be used with any exponential family distribution over the cliques in the graph. Second, it can impose additional constraints on the marginal distributions. We use this second property to impose pair-wise marginal distribution constraints in some check nodes of the LDPC Tanner graph. These additional constraints allow decoding the received codeword when the BP decoder gets stuck. In this paper, we first present the new decoding algorithm, whose complexity is identical to the BP decoder, and we then prove that it is able to decode codewords with a larger fraction of erasures, as the block size tends to infinity. The proposed algorithm can be also understood as a simplification of the Maxwell decoder, but without its computational complexity. We also illustrate that the new algorithm outperforms the BP decoder for finite block-size codes.
Djuric, Petar M; Closas, Pau; Bugallo, Monica F; Miguez, Joaquin
Evaluation of a Method's Robustness Artículo en actas
En: 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3598–3601, IEEE, Dallas, 2010, ISSN: 1520-6149.
Resumen | Enlaces | BibTeX | Etiquetas: Electronic mail, Extraterrestrial measurements, Filtering, Gaussian processes, method's robustness, Random variables, robustness, sequential methods, Signal processing, statistical distributions, Telecommunications, uniform distribution, Wireless communication
@inproceedings{Djuric2010,
title = {Evaluation of a Method's Robustness},
author = {Petar M Djuric and Pau Closas and Monica F Bugallo and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5495921},
issn = {1520-6149},
year = {2010},
date = {2010-01-01},
booktitle = {2010 IEEE International Conference on Acoustics, Speech and Signal Processing},
pages = {3598--3601},
publisher = {IEEE},
address = {Dallas},
abstract = {In signal processing, it is typical to develop or use a method based on a given model. In practice, however, we almost never know the actual model and we hope that the assumed model is in the neighborhood of the true one. If deviations exist, the method may be more or less sensitive to them. Therefore, it is important to know more about this sensitivity, or in other words, how robust the method is to model deviations. To that end, it is useful to have a metric that can quantify the robustness of the method. In this paper we propose a procedure for developing a variety of metrics for measuring robustness. They are based on a discrete random variable that is generated from observed data and data generated according to past data and the adopted model. This random variable is uniform if the model is correct. When the model deviates from the true one, the distribution of the random variable deviates from the uniform distribution. One can then employ measures for differences between distributions in order to quantify robustness. In this paper we describe the proposed methodology and demonstrate it with simulated data.},
keywords = {Electronic mail, Extraterrestrial measurements, Filtering, Gaussian processes, method's robustness, Random variables, robustness, sequential methods, Signal processing, statistical distributions, Telecommunications, uniform distribution, Wireless communication},
pubstate = {published},
tppubtype = {inproceedings}
}
In signal processing, it is typical to develop or use a method based on a given model. In practice, however, we almost never know the actual model and we hope that the assumed model is in the neighborhood of the true one. If deviations exist, the method may be more or less sensitive to them. Therefore, it is important to know more about this sensitivity, or in other words, how robust the method is to model deviations. To that end, it is useful to have a metric that can quantify the robustness of the method. In this paper we propose a procedure for developing a variety of metrics for measuring robustness. They are based on a discrete random variable that is generated from observed data and data generated according to past data and the adopted model. This random variable is uniform if the model is correct. When the model deviates from the true one, the distribution of the random variable deviates from the uniform distribution. One can then employ measures for differences between distributions in order to quantify robustness. In this paper we describe the proposed methodology and demonstrate it with simulated data.
Salamanca, Luis; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando
Bayesian BCJR for Channel Equalization and Decoding Artículo en actas
En: 2010 IEEE International Workshop on Machine Learning for Signal Processing, pp. 53–58, IEEE, Kittila, 2010, ISSN: 1551-2541.
Resumen | Enlaces | BibTeX | Etiquetas: a posteriori probability, Bayes methods, Bayesian BCJR, Bayesian methods, Bit error rate, channel decoding, channel estate information, Channel estimation, Decoding, digital communication, digital communications, equalisers, Equalizers, error statistics, Markov processes, Maximum likelihood decoding, maximum likelihood estimation, multipath channel, probabilistic channel equalization, Probability, single input single output model, SISO model, statistical information, Training
@inproceedings{Salamanca2010,
title = {Bayesian BCJR for Channel Equalization and Decoding},
author = {Luis Salamanca and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5589201},
issn = {1551-2541},
year = {2010},
date = {2010-01-01},
booktitle = {2010 IEEE International Workshop on Machine Learning for Signal Processing},
pages = {53--58},
publisher = {IEEE},
address = {Kittila},
abstract = {In this paper we focus on the probabilistic channel equalization in digital communications. We face the single input single output (SISO) model to show how the statistical information about the multipath channel can be exploited to further improve our estimation of the a posteriori probabilities (APP) during the equalization process. We consider not only the uncertainty due to the noise in the channel, but also in the estimate of the channel estate information (CSI). Thus, we resort to a Bayesian approach for the computation of the APP. This novel algorithm has the same complexity as the BCJR, exhibiting lower bit error rate at the output of the channel decoder than the standard BCJR that considers maximum likelihood (ML) to estimate the CSI.},
keywords = {a posteriori probability, Bayes methods, Bayesian BCJR, Bayesian methods, Bit error rate, channel decoding, channel estate information, Channel estimation, Decoding, digital communication, digital communications, equalisers, Equalizers, error statistics, Markov processes, Maximum likelihood decoding, maximum likelihood estimation, multipath channel, probabilistic channel equalization, Probability, single input single output model, SISO model, statistical information, Training},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we focus on the probabilistic channel equalization in digital communications. We face the single input single output (SISO) model to show how the statistical information about the multipath channel can be exploited to further improve our estimation of the a posteriori probabilities (APP) during the equalization process. We consider not only the uncertainty due to the noise in the channel, but also in the estimate of the channel estate information (CSI). Thus, we resort to a Bayesian approach for the computation of the APP. This novel algorithm has the same complexity as the BCJR, exhibiting lower bit error rate at the output of the channel decoder than the standard BCJR that considers maximum likelihood (ML) to estimate the CSI.
Vinuelas-Peris, Pablo; Artés-Rodríguez, Antonio
Bayesian Joint Recovery of Correlated Signals in Distributed Compressed Sensing Artículo en actas
En: 2010 2nd International Workshop on Cognitive Information Processing, pp. 382–387, IEEE, Elba, 2010, ISBN: 978-1-4244-6459-3.
Resumen | Enlaces | BibTeX | Etiquetas: Bayes methods, Bayesian joint recovery, Bayesian methods, correlated signal, Correlation, correlation methods, Covariance matrix, Dictionaries, distributed compressed sensing, matrix decomposition, Noise measurement, sensors, sparse component correlation coefficient
@inproceedings{Vinuelas-Peris2010,
title = {Bayesian Joint Recovery of Correlated Signals in Distributed Compressed Sensing},
author = {Pablo Vinuelas-Peris and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5604103},
isbn = {978-1-4244-6459-3},
year = {2010},
date = {2010-01-01},
booktitle = {2010 2nd International Workshop on Cognitive Information Processing},
pages = {382--387},
publisher = {IEEE},
address = {Elba},
abstract = {In this paper we address the problem of Distributed Compressed Sensing (DCS) of correlated signals. We model the correlation using the sparse components correlation coefficient of signals, a general and simple measure. We develop an sparse Bayesian learning method for this setting, that can be applied to both random and optimized projection matrices. As a result, we obtain a reduction of the number of measurements needed for a given recovery error that is dependent on the correlation coefficient, as shown by computer simulations in different scenarios.},
keywords = {Bayes methods, Bayesian joint recovery, Bayesian methods, correlated signal, Correlation, correlation methods, Covariance matrix, Dictionaries, distributed compressed sensing, matrix decomposition, Noise measurement, sensors, sparse component correlation coefficient},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we address the problem of Distributed Compressed Sensing (DCS) of correlated signals. We model the correlation using the sparse components correlation coefficient of signals, a general and simple measure. We develop an sparse Bayesian learning method for this setting, that can be applied to both random and optimized projection matrices. As a result, we obtain a reduction of the number of measurements needed for a given recovery error that is dependent on the correlation coefficient, as shown by computer simulations in different scenarios.
Achutegui, Katrin; Rodas, Javier; Escudero, Carlos J; Miguez, Joaquin
A Model-Switching Sequential Monte Carlo Algorithm for Indoor Tracking with Experimental RSS Data Artículo en actas
En: 2010 International Conference on Indoor Positioning and Indoor Navigation, pp. 1–8, IEEE, Zurich, 2010, ISBN: 978-1-4244-5862-2.
Resumen | Enlaces | BibTeX | Etiquetas: Approximation methods, Computational modeling, Data models, generalized IMM system, GIMM approach, indoor radio, Indoor tracking, Kalman filters, maneuvering target motion, Mathematical model, model switching sequential Monte Carlo algorithm, Monte Carlo methods, multipath propagation, multiple model interaction, propagation environment, radio receivers, radio tracking, radio transmitters, random processes, Rao-Blackwellized sequential Monte Carlo tracking, received signal strength, RSS data, sensors, state space model, target position dependent data, transmitter-to-receiver distance, wireless technology
@inproceedings{Achutegui2010,
title = {A Model-Switching Sequential Monte Carlo Algorithm for Indoor Tracking with Experimental RSS Data},
author = {Katrin Achutegui and Javier Rodas and Carlos J Escudero and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5648053},
isbn = {978-1-4244-5862-2},
year = {2010},
date = {2010-01-01},
booktitle = {2010 International Conference on Indoor Positioning and Indoor Navigation},
pages = {1--8},
publisher = {IEEE},
address = {Zurich},
abstract = {In this paper we address the problem of indoor tracking using received signal strength (RSS) as position-dependent data. This type of measurements are very appealing because they can be easily obtained with a variety of (inexpensive) wireless technologies. However, the extraction of accurate location information from RSS in indoor scenarios is not an easy task. Due to the multipath propagation, it is hard to adequately model the correspondence between the received power and the transmitter-to-receiver distance. For that reason, we propose the use of a compound model that combines several sub-models, whose parameters are adjusted to different propagation environments. This methodology, called Interacting Multiple Models (IMM), has been used in the past either for modeling the motion of maneuvering targets or the relationship between the target position and the observations. Here, we extend its application to handle both types of uncertainty simultaneously and we refer to the resulting state-space model as a generalized IMM (GIMM) system. The flexibility of the GIMM approach is attained at the expense of an increase in the number of random processes that must be accurately tracked. To overcome this difficulty, we introduce a Rao-Blackwellized sequential Monte Carlo tracking algorithm that exhibits good performance both with synthetic and experimental data.},
keywords = {Approximation methods, Computational modeling, Data models, generalized IMM system, GIMM approach, indoor radio, Indoor tracking, Kalman filters, maneuvering target motion, Mathematical model, model switching sequential Monte Carlo algorithm, Monte Carlo methods, multipath propagation, multiple model interaction, propagation environment, radio receivers, radio tracking, radio transmitters, random processes, Rao-Blackwellized sequential Monte Carlo tracking, received signal strength, RSS data, sensors, state space model, target position dependent data, transmitter-to-receiver distance, wireless technology},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we address the problem of indoor tracking using received signal strength (RSS) as position-dependent data. This type of measurements are very appealing because they can be easily obtained with a variety of (inexpensive) wireless technologies. However, the extraction of accurate location information from RSS in indoor scenarios is not an easy task. Due to the multipath propagation, it is hard to adequately model the correspondence between the received power and the transmitter-to-receiver distance. For that reason, we propose the use of a compound model that combines several sub-models, whose parameters are adjusted to different propagation environments. This methodology, called Interacting Multiple Models (IMM), has been used in the past either for modeling the motion of maneuvering targets or the relationship between the target position and the observations. Here, we extend its application to handle both types of uncertainty simultaneously and we refer to the resulting state-space model as a generalized IMM (GIMM) system. The flexibility of the GIMM approach is attained at the expense of an increase in the number of random processes that must be accurately tracked. To overcome this difficulty, we introduce a Rao-Blackwellized sequential Monte Carlo tracking algorithm that exhibits good performance both with synthetic and experimental data.
Helander, E; Silén, H; Miguez, Joaquin; Gabbouj, M
Maximum a Posteriori Voice Conversion Using Sequential Monte Carlo Methods Artículo en actas
En: Eleventh Annual Conference of the International Speech Communication Association (INTERSPEECH), Makuhari, Chiba, Japan, 2010.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Helander2010,
title = {Maximum a Posteriori Voice Conversion Using Sequential Monte Carlo Methods},
author = {E Helander and H Sil\'{e}n and Joaquin Miguez and M Gabbouj},
url = {http://www.isca-speech.org/archive/interspeech_2010/i10_1716.html},
year = {2010},
date = {2010-01-01},
booktitle = {Eleventh Annual Conference of the International Speech Communication Association (INTERSPEECH)},
address = {Makuhari, Chiba, Japan},
abstract = {Many voice conversion algorithms are based on frame-wise mapping from source features into target features. This ignores the inherent temporal continuity that is present in speech and can degrade the subjective quality. In this paper, we propose to optimize the speech feature sequence after a frame-based conversion algorithm has been applied. In particular, we select the sequence of speech features through the minimization of a cost function that involves both the conversion error and the smoothness of the sequence. The estimation problem is solved using sequential Monte Carlo methods. Both subjective and objective results show the effectiveness of the method.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Many voice conversion algorithms are based on frame-wise mapping from source features into target features. This ignores the inherent temporal continuity that is present in speech and can degrade the subjective quality. In this paper, we propose to optimize the speech feature sequence after a frame-based conversion algorithm has been applied. In particular, we select the sequence of speech features through the minimization of a cost function that involves both the conversion error and the smoothness of the sequence. The estimation problem is solved using sequential Monte Carlo methods. Both subjective and objective results show the effectiveness of the method.
Salamanca, Luis; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando
Channel Decoding with a Bayesian Equalizer Artículo en actas
En: 2010 IEEE International Symposium on Information Theory, pp. 1998–2002, IEEE, Austin, TX, 2010, ISBN: 978-1-4244-7892-7.
Resumen | Enlaces | BibTeX | Etiquetas: a posteriori probability, Bayesian equalizer, Bayesian methods, BER, Bit error rate, Channel Coding, channel decoding, channel estate information, Communication channels, Decoding, equalisers, Equalizers, error statistics, low-density parity-check decoders, LPDC decoders, Maximum likelihood decoding, maximum likelihood detection, maximum likelihood estimation, Noise reduction, parity check codes, Probability, Uncertainty
@inproceedings{Salamanca2010a,
title = {Channel Decoding with a Bayesian Equalizer},
author = {Luis Salamanca and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5513348},
isbn = {978-1-4244-7892-7},
year = {2010},
date = {2010-01-01},
booktitle = {2010 IEEE International Symposium on Information Theory},
pages = {1998--2002},
publisher = {IEEE},
address = {Austin, TX},
abstract = {Low-density parity-check (LPDC) decoders assume the channel estate information (CSI) is known and they have the true a posteriori probability (APP) for each transmitted bit. But in most cases of interest, the CSI needs to be estimated with the help of a short training sequence and the LDPC decoder has to decode the received word using faulty APP estimates. In this paper, we study the uncertainty in the CSI estimate and how it affects the bit error rate (BER) output by the LDPC decoder. To improve these APP estimates, we propose a Bayesian equalizer that takes into consideration not only the uncertainty due to the noise in the channel, but also the uncertainty in the CSI estimate, reducing the BER after the LDPC decoder.},
keywords = {a posteriori probability, Bayesian equalizer, Bayesian methods, BER, Bit error rate, Channel Coding, channel decoding, channel estate information, Communication channels, Decoding, equalisers, Equalizers, error statistics, low-density parity-check decoders, LPDC decoders, Maximum likelihood decoding, maximum likelihood detection, maximum likelihood estimation, Noise reduction, parity check codes, Probability, Uncertainty},
pubstate = {published},
tppubtype = {inproceedings}
}
Low-density parity-check (LPDC) decoders assume the channel estate information (CSI) is known and they have the true a posteriori probability (APP) for each transmitted bit. But in most cases of interest, the CSI needs to be estimated with the help of a short training sequence and the LDPC decoder has to decode the received word using faulty APP estimates. In this paper, we study the uncertainty in the CSI estimate and how it affects the bit error rate (BER) output by the LDPC decoder. To improve these APP estimates, we propose a Bayesian equalizer that takes into consideration not only the uncertainty due to the noise in the channel, but also the uncertainty in the CSI estimate, reducing the BER after the LDPC decoder.
Perez-Cruz, Fernando; Kulkarni, S R
Robust and Low Complexity Distributed Kernel Least Squares Learning in Sensor Networks Artículo de revista
En: IEEE Signal Processing Letters, vol. 17, no. 4, pp. 355–358, 2010, ISSN: 1070-9908.
Resumen | Enlaces | BibTeX | Etiquetas: communication complexity, Consensus, distributed learning, kernel methods, learning (artificial intelligence), low complexity distributed kernel least squares le, message passing, message-passing algorithms, robust nonparametric statistics, sensor network learning, sensor networks, telecommunication computing, Wireless Sensor Networks
@article{Perez-Cruz2010,
title = {Robust and Low Complexity Distributed Kernel Least Squares Learning in Sensor Networks},
author = {Fernando Perez-Cruz and S R Kulkarni},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5395679},
issn = {1070-9908},
year = {2010},
date = {2010-01-01},
journal = {IEEE Signal Processing Letters},
volume = {17},
number = {4},
pages = {355--358},
abstract = {We present a novel mechanism for consensus building in sensor networks. The proposed algorithm has three main properties that make it suitable for sensor network learning. First, the proposed algorithm is based on robust nonparametric statistics and thereby needs little prior knowledge about the network and the function that needs to be estimated. Second, the algorithm uses only local information about the network and it communicates only with nearby sensors. Third, the algorithm is completely asynchronous and robust. It does not need to coordinate the sensors to estimate the underlying function and it is not affected if other sensors in the network stop working. Therefore, the proposed algorithm is an ideal candidate for sensor networks deployed in remote and inaccessible areas, which might need to change their objective once they have been set up.},
keywords = {communication complexity, Consensus, distributed learning, kernel methods, learning (artificial intelligence), low complexity distributed kernel least squares le, message passing, message-passing algorithms, robust nonparametric statistics, sensor network learning, sensor networks, telecommunication computing, Wireless Sensor Networks},
pubstate = {published},
tppubtype = {article}
}
We present a novel mechanism for consensus building in sensor networks. The proposed algorithm has three main properties that make it suitable for sensor network learning. First, the proposed algorithm is based on robust nonparametric statistics and thereby needs little prior knowledge about the network and the function that needs to be estimated. Second, the algorithm uses only local information about the network and it communicates only with nearby sensors. Third, the algorithm is completely asynchronous and robust. It does not need to coordinate the sensors to estimate the underlying function and it is not affected if other sensors in the network stop working. Therefore, the proposed algorithm is an ideal candidate for sensor networks deployed in remote and inaccessible areas, which might need to change their objective once they have been set up.
Carballo, Juan J; Baca-García, Enrique; Blanco, Carlos; Perez-Rodriguez, Mercedes M; Jimenez-Arriero, Miguel A; Artés-Rodríguez, Antonio; Rynn, Moira; Shaffer, David; Oquendo, Maria A
Stability of Childhood Anxiety Disorder Diagnoses: a Follow-Up Naturalistic Study in Psychiatric Care Artículo de revista
En: European child & adolescent psychiatry, vol. 19, no. 4, pp. 395–403, 2010, ISSN: 1435-165X.
Resumen | Enlaces | BibTeX | Etiquetas: Adolescent, Ambulatory Care, Ambulatory Care: utilization, Anxiety Disorders, Anxiety Disorders: diagnosis, Anxiety Disorders: epidemiology, Catchment Area (Health), Child, Cohort Studies, Female, Follow-Up Studies, Humans, International Classification of Diseases, Male, Mental Health Services, Mental Health Services: utilization, Preschool, Prospective Studies, Severity of Illness Index, Spain, Spain: epidemiology
@article{Carballo2010,
title = {Stability of Childhood Anxiety Disorder Diagnoses: a Follow-Up Naturalistic Study in Psychiatric Care},
author = {Juan J Carballo and Enrique Baca-Garc\'{i}a and Carlos Blanco and Mercedes M Perez-Rodriguez and Miguel A Jimenez-Arriero and Antonio Art\'{e}s-Rodr\'{i}guez and Moira Rynn and David Shaffer and Maria A Oquendo},
url = {http://www.ncbi.nlm.nih.gov/pubmed/19826859},
issn = {1435-165X},
year = {2010},
date = {2010-01-01},
journal = {European child \& adolescent psychiatry},
volume = {19},
number = {4},
pages = {395--403},
abstract = {Few studies have examined the stability of major psychiatric disorders in pediatric psychiatric clinical populations. The objective of this study was to examine the long-term stability of anxiety diagnoses starting with pre-school age children through adolescence evaluated at multiple time points. Prospective cohort study was conducted of all children and adolescents receiving psychiatric care at all pediatric psychiatric clinics belonging to two catchment areas in Madrid, Spain, between 1 January, 1992 and 30 April, 2006. Patients were selected from among 24,163 children and adolescents who received psychiatric care. Patients had to have a diagnosis of an ICD-10 anxiety disorder during at least one of the consultations and had to have received psychiatric care for the anxiety disorder. We grouped anxiety disorder diagnoses according to the following categories: phobic disorders, social anxiety disorders, obsessive-compulsive disorder (OCD), stress-related disorders, and \"{o}ther" anxiety disorders which, among others, included generalized anxiety disorder, and panic disorder. Complementary indices of diagnostic stability were calculated. As much as 1,869 subjects were included and had 27,945 psychiatric/psychological consultations. The stability of all ICD-10 anxiety disorder categories studied was high regardless of the measure of diagnostic stability used. Phobic and social anxiety disorders showed the highest diagnostic stability, whereas OCD and \"{o}ther" anxiety disorders showed the lowest diagnostic stability. No significant sex differences were observed on the diagnostic stability of the anxiety disorder categories studied. Diagnostic stability measures for phobic, social anxiety, and \"{o}ther" anxiety disorder diagnoses varied depending on the age at first evaluation. In this clinical pediatric outpatient sample it appears that phobic, social anxiety, and stress-related disorder diagnoses in children and adolescents treated in community outpatient services may have high diagnostic stability.},
keywords = {Adolescent, Ambulatory Care, Ambulatory Care: utilization, Anxiety Disorders, Anxiety Disorders: diagnosis, Anxiety Disorders: epidemiology, Catchment Area (Health), Child, Cohort Studies, Female, Follow-Up Studies, Humans, International Classification of Diseases, Male, Mental Health Services, Mental Health Services: utilization, Preschool, Prospective Studies, Severity of Illness Index, Spain, Spain: epidemiology},
pubstate = {published},
tppubtype = {article}
}
Few studies have examined the stability of major psychiatric disorders in pediatric psychiatric clinical populations. The objective of this study was to examine the long-term stability of anxiety diagnoses starting with pre-school age children through adolescence evaluated at multiple time points. Prospective cohort study was conducted of all children and adolescents receiving psychiatric care at all pediatric psychiatric clinics belonging to two catchment areas in Madrid, Spain, between 1 January, 1992 and 30 April, 2006. Patients were selected from among 24,163 children and adolescents who received psychiatric care. Patients had to have a diagnosis of an ICD-10 anxiety disorder during at least one of the consultations and had to have received psychiatric care for the anxiety disorder. We grouped anxiety disorder diagnoses according to the following categories: phobic disorders, social anxiety disorders, obsessive-compulsive disorder (OCD), stress-related disorders, and öther" anxiety disorders which, among others, included generalized anxiety disorder, and panic disorder. Complementary indices of diagnostic stability were calculated. As much as 1,869 subjects were included and had 27,945 psychiatric/psychological consultations. The stability of all ICD-10 anxiety disorder categories studied was high regardless of the measure of diagnostic stability used. Phobic and social anxiety disorders showed the highest diagnostic stability, whereas OCD and öther" anxiety disorders showed the lowest diagnostic stability. No significant sex differences were observed on the diagnostic stability of the anxiety disorder categories studied. Diagnostic stability measures for phobic, social anxiety, and öther" anxiety disorder diagnoses varied depending on the age at first evaluation. In this clinical pediatric outpatient sample it appears that phobic, social anxiety, and stress-related disorder diagnoses in children and adolescents treated in community outpatient services may have high diagnostic stability.