@article{Murillo-Fuentes2009,

title = {Gaussian Process Regressors for Multiuser Detection in DS-CDMA Systems},

author = {Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5201027},

issn = {0090-6778},

year  = {2009},

date = {2009-01-01},

journal = {IEEE Transactions on Communications},

volume = {57},

number = {8},

pages = {2339--2347},

abstract = {In this paper we present Gaussian processes for Regression (GPR) as a novel detector for CDMA digital communications. Particularly, we propose GPR for constructing analytical nonlinear multiuser detectors in CDMA communication systems. GPR can easily compute the parameters that describe its nonlinearities by maximum likelihood. Thereby, no cross-validation is needed, as it is typically used in nonlinear estimation procedures. The GPR solution is analytical, given its parameters, and it does not need to solve an optimization problem for building the nonlinear estimator. These properties provide fast and accurate learning, two major issues in digital communications. The GPR with a linear decision function can be understood as a regularized MMSE detector, in which the regularization parameter is optimally set. We also show the GPR receiver to be a straightforward nonlinear extension of the linear minimum mean square error (MMSE) criterion, widely used in the design of these receivers. We argue the benefits of this new approach in short codes CDMA systems where little information on the users' codes, users' amplitudes or the channel is available. The paper includes some experiments to show that GPR outperforms linear (MMSE) and nonlinear (SVM) state-ofthe- art solutions.},

keywords = {analytical nonlinear multiuser detectors, code division multiple access, communication systems, Detectors, digital communication, digital communications, DS-CDMA systems, Gaussian process for regressi, Gaussian process regressors, Gaussian processes, GPR, Ground penetrating radar, least mean squares methods, maximum likelihood, maximum likelihood detection, maximum likelihood estimation, mean square error methods, minimum mean square error, MMSE, Multiaccess communication, Multiuser detection, nonlinear estimator, nonlinear state-ofthe- art solutions, radio receivers, Receivers, regression analysis, Support vector machines},

pubstate = {published},

tppubtype = {article}

}

@article{Marino2009,

title = {Monte Carlo Method for Adaptively Estimating the Unknown Parameters and the Dynamic State of Chaotic Systems},

author = {In\'{e}s P. Mari\~{n}o and Joaquin Miguez and Riccardo Meucci},

url = {http://link.aps.org/doi/10.1103/PhysRevE.79.056218},

issn = {1539-3755},

year  = {2009},

date = {2009-01-01},

journal = {Physical Review E},

volume = {79},

number = {5},

pages = {056218},

publisher = {American Physical Society},

abstract = {We propose a Monte Carlo methodology for the joint estimation of unobserved dynamic variables and unknown static parameters in chaotic systems. The technique is sequential, i.e., it updates the variable and parameter estimates recursively as new observations become available, and, hence, suitable for online implementation. We demonstrate the validity of the method by way of two examples. In the first one, we tackle the estimation of all the dynamic variables and one unknown parameter of a five-dimensional nonlinear model using a time series of scalar observations experimentally collected from a chaotic CO2$CO2 laser. In the second example, we address the estimation of the two dynamic variables and the phase parameter of a numerical model commonly employed to represent the dynamics of optoelectronic feedback loops designed for chaotic communications over fiber-optic links.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
CerrarWe propose a Monte Carlo methodology for the joint estimation of unobserved dynamic variables and unknown static parameters in chaotic systems. The technique is sequential, i.e., it updates the variable and parameter estimates recursively as new observations become available, and, hence, suitable for online implementation. We demonstrate the validity of the method by way of two examples. In the first one, we tackle the estimation of all the dynamic variables and one unknown parameter of a five-dimensional nonlinear model using a time series of scalar observations experimentally collected from a chaotic CO2<math display="inline"><mrow><msub><mrow><mtext>CO<mn>2 laser. In the second example, we address the estimation of the two dynamic variables and the phase parameter of a numerical model commonly employed to represent the dynamics of optoelectronic feedback loops designed for chaotic communications over fiber-optic links.Cerrarhttp://link.aps.org/doi/10.1103/PhysRevE.79.056218Cerrar Vazquez, Manuel A;  Miguez, JoaquinMaximum-Likelihood Sequence Detection in Time- and Frequency-Selective MIMO Channels With Unknown Order Artículo de revista En: IEEE Transactions on Vehicular Technology, vol. 58, no. 1, pp. 499–504, 2009, ISSN: 0018-9545.Resumen | Enlaces | BibTeX | Etiquetas: channel impulse response, channel order estimation, CIR, frequency-selective multiple-input-multiple-output, joint channel and data estimation, maximum likelihood detection, maximum-likelihood sequence detection, MIMO channels, MIMO communication, MLSD, Multiple Input Multiple Output (MIMO), multiple-input–multiple-output (MIMO), per-survivor processing, per-survivor processing (PSP), telecommunication channels, time-selective multiple-input-multiple-output chan@article{Vazquez2009,
title = {Maximum-Likelihood Sequence Detection in Time- and Frequency-Selective MIMO Channels With Unknown Order},
author = {Manuel A Vazquez and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4510724},
issn = {0018-9545},
year  = {2009},
date = {2009-01-01},
journal = {IEEE Transactions on Vehicular Technology},
volume = {58},
number = {1},
pages = {499--504},
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), which is also referred to as the channel order, is known. However, this is not true in most practical situations, and it is a common approach to overestimate the channel order to avoid the serious performance degradation that occurs when the CIR length is underestimated. Unfortunately, the computational complexity of maximum-likelihood sequence detection (MLSD) in frequency-selective channels exponentially grows with the channel order; hence, overestimation can actually be undesirable because it leads to more expensive and inefficient receivers. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. 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 is designed to work with time-selective channels. In addition to the analytical derivation of the algorithm, we provide computer simulation results that illustrate the effectiveness of the resulting receiver.},
keywords = {channel impulse response, channel order estimation, CIR, frequency-selective multiple-input-multiple-output, joint channel and data estimation, maximum likelihood detection, maximum-likelihood sequence detection, MIMO channels, MIMO communication, MLSD, Multiple Input Multiple Output (MIMO), multiple-input\textendashmultiple-output (MIMO), per-survivor processing, per-survivor processing (PSP), telecommunication channels, time-selective multiple-input-multiple-output chan},
pubstate = {published},
tppubtype = {article}
}
CerrarIn the equalization of frequency-selective multiple-input-multiple-output (MIMO) channels, it is usually assumed that the length of the channel impulse response (CIR), which is also referred to as the channel order, is known. However, this is not true in most practical situations, and it is a common approach to overestimate the channel order to avoid the serious performance degradation that occurs when the CIR length is underestimated. Unfortunately, the computational complexity of maximum-likelihood sequence detection (MLSD) in frequency-selective channels exponentially grows with the channel order; hence, overestimation can actually be undesirable because it leads to more expensive and inefficient receivers. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. 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 is designed to work with time-selective channels. In addition to the analytical derivation of the algorithm, we provide computer simulation results that illustrate the effectiveness of the resulting receiver.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4510724Cerrar Koch, Tobias;  Lapidoth, Amos;  Sotiriadis, Paul PChannels That Heat Up Artículo de revista En: IEEE Transactions on Information Theory, vol. 55, no. 8, pp. 3594–3612, 2009, ISSN: 0018-9448.Resumen | Enlaces | BibTeX | Etiquetas: additive noise channel, Capacity per unit cost, channel capacity, channels with memory, cooling, electronic circuits, heat dissipation, heat sinks, high signal-to-noise ratio, high signal-to-noise ratio (SNR), intrinsic thermal noise, low transmit power, network analysis, noise variance, on-chip communication, thermal noise@article{Koch2009,
title = {Channels That Heat Up},
author = {Tobias Koch and Amos Lapidoth and Paul P Sotiriadis},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5165190},
issn = {0018-9448},
year  = {2009},
date = {2009-01-01},
journal = {IEEE Transactions on Information Theory},
volume = {55},
number = {8},
pages = {3594--3612},
abstract = {This paper considers an additive noise channel where the time-A; noise variance is a weighted sum of the squared magnitudes of the previous channel inputs plus a constant. This channel model accounts for the dependence of the intrinsic thermal noise on the data due to the heat dissipation associated with the transmission of data in electronic circuits: the data determine the transmitted signal, which in turn heats up the circuit and thus influences the power of the thermal noise. The capacity of this channel (both with and without feedback) is studied at low transmit powers and at high transmit powers. At low transmit powers, the slope of the capacity-versus-power curve at zero is computed and it is shown that the heating-up effect is beneficial. At high transmit powers, conditions are determined under which the capacity is bounded, i.e., under which the capacity does not grow to infinity as the allowed average power tends to infinity.},
keywords = {additive noise channel, Capacity per unit cost, channel capacity, channels with memory, cooling, electronic circuits, heat dissipation, heat sinks, high signal-to-noise ratio, high signal-to-noise ratio (SNR), intrinsic thermal noise, low transmit power, network analysis, noise variance, on-chip communication, thermal noise},
pubstate = {published},
tppubtype = {article}
}
CerrarThis paper considers an additive noise channel where the time-A; noise variance is a weighted sum of the squared magnitudes of the previous channel inputs plus a constant. This channel model accounts for the dependence of the intrinsic thermal noise on the data due to the heat dissipation associated with the transmission of data in electronic circuits: the data determine the transmitted signal, which in turn heats up the circuit and thus influences the power of the thermal noise. The capacity of this channel (both with and without feedback) is studied at low transmit powers and at high transmit powers. At low transmit powers, the slope of the capacity-versus-power curve at zero is computed and it is shown that the heating-up effect is beneficial. At high transmit powers, conditions are determined under which the capacity is bounded, i.e., under which the capacity does not grow to infinity as the allowed average power tends to infinity.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5165190Cerrar Lázaro, Marcelino;  González-Olasola, JonathanBlind Equalization Using the IRWLS Formulation of the Support Vector Machine Artículo de revista En: Signal Processing, vol. 89, no. 7, pp. 1436–1445, 2009, ISSN: 01651684.Resumen | Enlaces | BibTeX | Etiquetas: @article{Lazaro2009b,
title = {Blind Equalization Using the IRWLS Formulation of the Support Vector Machine},
author = {Marcelino L\'{a}zaro and Jonathan Gonz\'{a}lez-Olasola},
url = {http://www.sciencedirect.com/science/article/pii/S0165168409000383},
issn = {01651684},
year  = {2009},
date = {2009-01-01},
journal = {Signal Processing},
volume = {89},
number = {7},
pages = {1436--1445},
abstract = {In this paper, using a common framework, we propose, analyze, and evaluate several variants of batch algorithms for blind equalization of SISO channels. They are based on the iterative re-weighted least square (IRWLS) solution for the support vector machine (SVM). The proposed methods combine the conventional cost function of the SVM with classical error functions applied to blind equalization: Sato's and Godard's error functions are included in the penalty term of the SVM. The relationship of these batch algorithms with conventional equalization and regularization techniques is analyzed in the paper. Simulation experiments performed over a relevant set of channels show that the proposed equalization methods perform better than traditional cumulant-based methods: they require a lower number of data samples to achieve the same equalization level and convergence ratio.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
CerrarIn this paper, using a common framework, we propose, analyze, and evaluate several variants of batch algorithms for blind equalization of SISO channels. They are based on the iterative re-weighted least square (IRWLS) solution for the support vector machine (SVM). The proposed methods combine the conventional cost function of the SVM with classical error functions applied to blind equalization: Sato's and Godard's error functions are included in the penalty term of the SVM. The relationship of these batch algorithms with conventional equalization and regularization techniques is analyzed in the paper. Simulation experiments performed over a relevant set of channels show that the proposed equalization methods perform better than traditional cumulant-based methods: they require a lower number of data samples to achieve the same equalization level and convergence ratio.Cerrarhttp://www.sciencedirect.com/science/article/pii/S0165168409000383Cerrar Goez, Roger;  Lazaro, MarcelinoTraining of Neural Classifiers by Separating Distributions at the Hidden Layer Artículo en actas En: 2009 IEEE International Workshop on Machine Learning for Signal Processing, pp. 1–6, IEEE, Grenoble, 2009, ISBN: 978-1-4244-4947-7.Resumen | Enlaces | BibTeX | Etiquetas: Artificial neural networks, Bayesian methods, Cost function, Curve fitting, Databases, Function approximation, Neural networks, Speech recognition, Support vector machine classification, Support vector machines@inproceedings{Goez2009,
title = {Training of Neural Classifiers by Separating Distributions at the Hidden Layer},
author = {Roger Goez and Marcelino Lazaro},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5306240},
isbn = {978-1-4244-4947-7},
year  = {2009},
date = {2009-01-01},
booktitle = {2009 IEEE International Workshop on Machine Learning for Signal Processing},
pages = {1--6},
publisher = {IEEE},
address = {Grenoble},
abstract = {A new cost function for training of binary classifiers based on neural networks is proposed. This cost function aims at separating the distributions for patterns of each class at the output of the hidden layer of the network. It has been implemented in a Generalized Radial Basis Function (GRBF) network and its performance has been evaluated under three different databases, showing advantages with respect to the conventional Mean Squared Error (MSE) cost function. With respect to the Support Vector Machine (SVM) classifier, the proposed method has also advantages both in terms of performance and complexity.},
keywords = {Artificial neural networks, Bayesian methods, Cost function, Curve fitting, Databases, Function approximation, Neural networks, Speech recognition, Support vector machine classification, Support vector machines},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarA new cost function for training of binary classifiers based on neural networks is proposed. This cost function aims at separating the distributions for patterns of each class at the output of the hidden layer of the network. It has been implemented in a Generalized Radial Basis Function (GRBF) network and its performance has been evaluated under three different databases, showing advantages with respect to the conventional Mean Squared Error (MSE) cost function. With respect to the Support Vector Machine (SVM) classifier, the proposed method has also advantages both in terms of performance and complexity.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5306240Cerrar Plata-Chaves, Jorge;  Lazaro, MarcelinoClosed-Form Error Exponent for the Neyman-Pearson Fusion of Markov Local Decisions Artículo en actas En: 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, pp. 533–536, IEEE, Cardiff, 2009, ISBN: 978-1-4244-2709-3.Resumen | Enlaces | BibTeX | Etiquetas: @inproceedings{Plata-Chaves2009,
title = {Closed-Form Error Exponent for the Neyman-Pearson Fusion of Markov Local Decisions},
author = {Jorge Plata-Chaves and Marcelino Lazaro},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=5278522},
isbn = {978-1-4244-2709-3},
year  = {2009},
date = {2009-01-01},
booktitle = {2009 IEEE/SP 15th Workshop on Statistical Signal Processing},
pages = {533--536},
publisher = {IEEE},
address = {Cardiff},
abstract = {In this correspondence, we derive a closed-form expression of the error exponent associated with the binary Neyman-Pearson test performed at the fusion center of a distributed detection system where a large number of local detectors take dependent binary decisions regarding a specific phenomenon. We assume that the sensors are equally spaced along a straight line, that their local decisions are taken with no kind of cooperation, and that they are transmitted to the fusion center over an error free parallel access channel. Under each one of the two possible hypothesis, H0 and H1 the correlation structure of the local binary decisions is modelled with a first-order binary Markov chain whose transition probabilities are linked with different physical parameters of the network. Through different simulations based on the error exponent and a deterministic physical model of the aforementioned transition probabilities we study the effect of network density on the overall detection performance.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarIn this correspondence, we derive a closed-form expression of the error exponent associated with the binary Neyman-Pearson test performed at the fusion center of a distributed detection system where a large number of local detectors take dependent binary decisions regarding a specific phenomenon. We assume that the sensors are equally spaced along a straight line, that their local decisions are taken with no kind of cooperation, and that they are transmitted to the fusion center over an error free parallel access channel. Under each one of the two possible hypothesis, H0 and H1 the correlation structure of the local binary decisions is modelled with a first-order binary Markov chain whose transition probabilities are linked with different physical parameters of the network. Through different simulations based on the error exponent and a deterministic physical model of the aforementioned transition probabilities we study the effect of network density on the overall detection performance.Cerrarhttp://ieeexplore.ieee.org/articleDetails.jsp?arnumber=5278522Cerrar Alvarez, Mauricio;  Luengo, David;  Lawrence, Neil DLatent Force Models Artículo en actas En: Conf. on Artificial Intelligence and Statistics, Clearwater Beach, 2009.BibTeX | Etiquetas: @inproceedings{Alvarez2009,
title = {Latent Force Models},
author = {Mauricio Alvarez and David Luengo and Neil D Lawrence},
year  = {2009},
date = {2009-01-01},
booktitle = {Conf. on Artificial Intelligence and Statistics},
address = {Clearwater Beach},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrar Lazaro, Marcelino;  Sanchez-Fernandez, Matilde;  Artés-Rodríguez, AntonioOptimal Sensor Selection in Binary Heterogeneous Sensor Networks Artículo de revista En: IEEE Transactions on Signal Processing, vol. 57, no. 4, pp. 1577–1587, 2009, ISSN: 1053-587X.Resumen | Enlaces | BibTeX | Etiquetas: binary heterogeneous sensor networks, discrimination performance, Energy scaling, object detection, optimal sensor selection, performance-cost ratio, sensor networks, sensor selection, symmetric Kullback-Leibler divergence, target detection problem, Wireless Sensor Networks@article{Lazaro2009bb,
title = {Optimal Sensor Selection in Binary Heterogeneous Sensor Networks},
author = {Marcelino Lazaro and Matilde Sanchez-Fernandez and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4749309},
issn = {1053-587X},
year  = {2009},
date = {2009-01-01},
journal = {IEEE Transactions on Signal Processing},
volume = {57},
number = {4},
pages = {1577--1587},
abstract = {We consider the problem of sensor selection in a heterogeneous sensor network when several types of binary sensors with different discrimination performance and costs are available. We want to analyze what is the optimal proportion of sensors of each class in a target detection problem when a total cost constraint is specified. We obtain the conditional distributions of the observations at the fusion center given the hypotheses, necessary to perform an optimal hypothesis test in this heterogeneous scenario. We characterize the performance of the tests by means of the symmetric Kullback-Leibler divergence, or J -divergence, applied to the conditional distributions under each hypothesis. By formulating the sensor selection as a constrained maximization problem, and showing the linearity of the J-divergence with the number of sensors of each class, we found that the optimal proportion of sensors is ldquowinner takes allrdquo like. The sensor class with the best performance/cost ratio is selected.},
keywords = {binary heterogeneous sensor networks, discrimination performance, Energy scaling, object detection, optimal sensor selection, performance-cost ratio, sensor networks, sensor selection, symmetric Kullback-Leibler divergence, target detection problem, Wireless Sensor Networks},
pubstate = {published},
tppubtype = {article}
}
CerrarWe consider the problem of sensor selection in a heterogeneous sensor network when several types of binary sensors with different discrimination performance and costs are available. We want to analyze what is the optimal proportion of sensors of each class in a target detection problem when a total cost constraint is specified. We obtain the conditional distributions of the observations at the fusion center given the hypotheses, necessary to perform an optimal hypothesis test in this heterogeneous scenario. We characterize the performance of the tests by means of the symmetric Kullback-Leibler divergence, or J -divergence, applied to the conditional distributions under each hypothesis. By formulating the sensor selection as a constrained maximization problem, and showing the linearity of the J-divergence with the number of sensors of each class, we found that the optimal proportion of sensors is ldquowinner takes allrdquo like. The sensor class with the best performance/cost ratio is selected.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4749309Cerrar Davidson, Pavel;  Vázquez, Manuel A;  Piche, RobertUninterrupted portable car navigation system using GPS, map and inertial sensors data Artículo en actas En: 2009 IEEE 13th International Symposium on Consumer Electronics, pp. 836-840, 2009.Enlaces | BibTeX | Etiquetas: @inproceedings{5156849,
title = {Uninterrupted portable car navigation system using GPS, map and inertial sensors data},
author = {Pavel Davidson and Manuel A V\'{a}zquez and Robert Piche},
doi = {10.1109/ISCE.2009.5156849},
year  = {2009},
date = {2009-01-01},
urldate = {2009-01-01},
booktitle = {2009 IEEE 13th International Symposium on Consumer Electronics},
pages = {836-840},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrardoi:10.1109/ISCE.2009.5156849Cerrar Parviainen, Jussi;  Vázquez, Manuel A;  Pekkalin, Olli;  Hautamaki, Jani;  Collin, Jussi;  Davidson, PavelUsing Doppler radar and MEMS gyro to augment DGPS for land vehicle navigation Artículo en actas En: 2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC), pp. 1690-1695, 2009.Enlaces | BibTeX | Etiquetas: @inproceedings{5281057,
title = {Using Doppler radar and MEMS gyro to augment DGPS for land vehicle navigation},
author = {Jussi Parviainen and Manuel A V\'{a}zquez and Olli Pekkalin and Jani Hautamaki and Jussi Collin and Pavel Davidson},
doi = {10.1109/CCA.2009.5281057},
year  = {2009},
date = {2009-01-01},
urldate = {2009-01-01},
booktitle = {2009 IEEE Control Applications, (CCA) \& Intelligent Control, (ISIC)},
pages = {1690-1695},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrardoi:10.1109/CCA.2009.5281057Cerrar2008 Vazquez-Vilar, Gonzalo;  Majjigi, Vinay;  Sezgin, Aydin;  Paulraj, ArogyaswamiMobility Dependent Feedback Scheme for point-to-point MIMO Systems Artículo en actas En: Asilomar Conference on Signals, Systems, and Computers (Asilomar SSC 2008), Pacific Grove, CA, U.S.A., 2008.BibTeX | Etiquetas: @inproceedings{asilomar2008,
title = {Mobility Dependent Feedback Scheme for point-to-point MIMO Systems},
author = {Gonzalo Vazquez-Vilar and Vinay Majjigi and Aydin Sezgin and Arogyaswami Paulraj},
year  = {2008},
date = {2008-10-01},
booktitle = {Asilomar Conference on Signals, Systems, and Computers (Asilomar SSC 2008)},
address = {Pacific Grove, CA, U.S.A.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrar Koch, Tobias;  Lapidoth, AmosOn Multipath Fading Channels at High SNR Artículo en actas En: 2008 IEEE International Symposium on Information Theory, pp. 1572–1576, IEEE, Toronto, 2008, ISBN: 978-1-4244-2256-2.Resumen | Enlaces | BibTeX | Etiquetas: channel capacity, Delay, discrete time systems, discrete-time channels, Entropy, Fading, fading channels, Frequency, Mathematical model, multipath channels, multipath fading channels, noncoherent channel model, Random variables, Signal to noise ratio, signal-to-noise ratios, SNR, statistics, Transmitters@inproceedings{Koch2008,
title = {On Multipath Fading Channels at High SNR},
author = {Tobias Koch and Amos Lapidoth},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4595252},
isbn = {978-1-4244-2256-2},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 IEEE International Symposium on Information Theory},
pages = {1572--1576},
publisher = {IEEE},
address = {Toronto},
abstract = {This paper studies the capacity of discrete-time multipath fading channels. It is assumed that the number of paths is finite, i.e., that the channel output is influenced by the present and by the L previous channel inputs. A noncoherent channel model is considered where neither transmitter nor receiver are cognizant of the fading's realization, but both are aware of its statistic. The focus is on capacity at high signal-to-noise ratios (SNR). In particular, the capacity pre-loglog-defined as the limiting ratio of the capacity to loglog(SNR) as SNR tends to infinity-is studied. It is shown that, irrespective of the number of paths L, the capacity pre-loglog is 1.},
keywords = {channel capacity, Delay, discrete time systems, discrete-time channels, Entropy, Fading, fading channels, Frequency, Mathematical model, multipath channels, multipath fading channels, noncoherent channel model, Random variables, Signal to noise ratio, signal-to-noise ratios, SNR, statistics, Transmitters},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarThis paper studies the capacity of discrete-time multipath fading channels. It is assumed that the number of paths is finite, i.e., that the channel output is influenced by the present and by the L previous channel inputs. A noncoherent channel model is considered where neither transmitter nor receiver are cognizant of the fading's realization, but both are aware of its statistic. The focus is on capacity at high signal-to-noise ratios (SNR). In particular, the capacity pre-loglog-defined as the limiting ratio of the capacity to loglog(SNR) as SNR tends to infinity-is studied. It is shown that, irrespective of the number of paths L, the capacity pre-loglog is 1.Cerrarhttp://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4595252Cerrar Vazquez, Manuel A;  Miguez, JoaquinA Per-Survivor Processing Algorithm for Maximum Likelihood Equalization of MIMO Channels with Unknown Order Artículo en actas En: 2008 International ITG Workshop on Smart Antennas, pp. 387–391, IEEE, Vienna, 2008, ISBN: 978-1-4244-1756-8.Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, channel impulse response, computational complexity, Computer science education, Computer Simulation, Degradation, Frequency, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood equalization, maximum likelihood estimation, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channels, MIMO communication, per-survivor processing algorithm, time-selective channels, Transmitting antennas@inproceedings{Vazquez2008,
title = {A Per-Survivor Processing Algorithm for Maximum Likelihood Equalization of MIMO Channels with Unknown Order},
author = {Manuel A Vazquez and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4475587},
isbn = {978-1-4244-1756-8},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 International ITG Workshop on Smart Antennas},
pages = {387--391},
publisher = {IEEE},
address = {Vienna},
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 possibly means overestimating the channel order, and is not desirable since the computational complexity of maximum likelihood sequence detection (MLSD) in frequency-selective channels grows exponentially with the channel order. In addition to that, the higher the channel order considered, the more the number of channel coefficients that need to be estimated from the same set of observations. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. 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 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 = {Channel estimation, channel impulse response, computational complexity, Computer science education, Computer Simulation, Degradation, Frequency, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood equalization, maximum likelihood estimation, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channels, MIMO communication, per-survivor processing algorithm, time-selective channels, Transmitting antennas},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarIn 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 possibly means overestimating the channel order, and is not desirable since the computational complexity of maximum likelihood sequence detection (MLSD) in frequency-selective channels grows exponentially with the channel order. In addition to that, the higher the channel order considered, the more the number of channel coefficients that need to be estimated from the same set of observations. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. 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 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 receiverCerrarhttp://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4475587Cerrar Miguez, JoaquinAnalysis of a Sequential Monte Carlo Optimization Methodology Artículo en actas En: 16th European Signal Processing Conference (EUSIPCO 2008, Lausanne, 2008.Resumen | Enlaces | BibTeX | Etiquetas: @inproceedings{Miguez2008,
title = {Analysis of a Sequential Monte Carlo Optimization Methodology},
author = {Joaquin Miguez},
url = {http://www.eurasip.org/Proceedings/Eusipco/Eusipco2008/papers/1569105254.pdf},
year  = {2008},
date = {2008-01-01},
booktitle = {16th European Signal Processing Conference (EUSIPCO 2008},
address = {Lausanne},
abstract = {We investigate a family of stochastic exploration methods that has been recently proposed to carry out estimation and prediction in discrete-time random dynamical systems. The key of the novel approach is to identify a cost function whose minima provide valid estimates of the system state at successive time instants. This function is recursively optimized using a sequential Monte Carlo minimization (SMCM) procedure which is similar to standard particle filtering algorithms but does not require a explicit probabilistic model to be imposed on the system. In this paper, we analyze the asymptotic convergence of SMCM methods and show that a properly designed algorithm produces a sequence of system-state estimates with individually minimal contributions to the cost function. We apply the SMCM method to a target tracking problem in order to illustrate how convergence is achieved in the way predicted by the theory.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarWe investigate a family of stochastic exploration methods that has been recently proposed to carry out estimation and prediction in discrete-time random dynamical systems. The key of the novel approach is to identify a cost function whose minima provide valid estimates of the system state at successive time instants. This function is recursively optimized using a sequential Monte Carlo minimization (SMCM) procedure which is similar to standard particle filtering algorithms but does not require a explicit probabilistic model to be imposed on the system. In this paper, we analyze the asymptotic convergence of SMCM methods and show that a properly designed algorithm produces a sequence of system-state estimates with individually minimal contributions to the cost function. We apply the SMCM method to a target tracking problem in order to illustrate how convergence is achieved in the way predicted by the theory.Cerrarhttp://www.eurasip.org/Proceedings/Eusipco/Eusipco2008/papers/1569105254.pdfCerrar Perez-Cruz, FernandoKullback-Leibler Divergence Estimation of Continuous Distributions Artículo en actas En: 2008 IEEE International Symposium on Information Theory, pp. 1666–1670, IEEE, Toronto, 2008, ISBN: 978-1-4244-2256-2.Resumen | Enlaces | BibTeX | Etiquetas: Convergence, density estimation, Density measurement, Entropy, Frequency estimation, H infinity control, information theory, k-nearest-neighbour density estimation, Kullback-Leibler divergence estimation, Machine learning, Mutual information, neuroscience, Random variables, statistical distributions, waiting-times distributions@inproceedings{Perez-Cruz2008,
title = {Kullback-Leibler Divergence Estimation of Continuous Distributions},
author = {Fernando Perez-Cruz},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4595271},
isbn = {978-1-4244-2256-2},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 IEEE International Symposium on Information Theory},
pages = {1666--1670},
publisher = {IEEE},
address = {Toronto},
abstract = {We present a method for estimating the KL divergence between continuous densities and we prove it converges almost surely. Divergence estimation is typically solved estimating the densities first. Our main result shows this intermediate step is unnecessary and that the divergence can be either estimated using the empirical cdf or k-nearest-neighbour density estimation, which does not converge to the true measure for finite k. The convergence proof is based on describing the statistics of our estimator using waiting-times distributions, as the exponential or Erlang. We illustrate the proposed estimators and show how they compare to existing methods based on density estimation, and we also outline how our divergence estimators can be used for solving the two-sample problem.},
keywords = {Convergence, density estimation, Density measurement, Entropy, Frequency estimation, H infinity control, information theory, k-nearest-neighbour density estimation, Kullback-Leibler divergence estimation, Machine learning, Mutual information, neuroscience, Random variables, statistical distributions, waiting-times distributions},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarWe present a method for estimating the KL divergence between continuous densities and we prove it converges almost surely. Divergence estimation is typically solved estimating the densities first. Our main result shows this intermediate step is unnecessary and that the divergence can be either estimated using the empirical cdf or k-nearest-neighbour density estimation, which does not converge to the true measure for finite k. The convergence proof is based on describing the statistics of our estimator using waiting-times distributions, as the exponential or Erlang. We illustrate the proposed estimators and show how they compare to existing methods based on density estimation, and we also outline how our divergence estimators can be used for solving the two-sample problem.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4595271Cerrar Perez-Cruz, Fernando;  Rodrigues, Miguel R D;  Verdu, SergioOptimal Precoding for Digital Subscriber Lines Artículo en actas En: 2008 IEEE International Conference on Communications, pp. 1200–1204, IEEE, Beijing, 2008, ISBN: 978-1-4244-2075-9.Resumen | Enlaces | BibTeX | Etiquetas: Bit error rate, channel matrix diagonalization, Communications Society, Computer science, digital subscriber lines, DSL, Equations, fixed-point equation, Gaussian channels, least mean squares methods, linear codes, matrix algebra, MIMO, MIMO communication, MIMO Gaussian channel, minimum mean squared error method, MMSE, multiple-input multiple-output communication, Mutual information, optimal linear precoder, precoding, Telecommunications, Telephony@inproceedings{Perez-Cruz2008a,
title = {Optimal Precoding for Digital Subscriber Lines},
author = {Fernando Perez-Cruz and Miguel R D Rodrigues and Sergio Verdu},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4533270},
isbn = {978-1-4244-2075-9},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 IEEE International Conference on Communications},
pages = {1200--1204},
publisher = {IEEE},
address = {Beijing},
abstract = {We determine the linear precoding policy that maximizes the mutual information for general multiple-input multiple-output (MIMO) Gaussian channels with arbitrary input distributions, by capitalizing on the relationship between mutual information and minimum mean squared error (MMSE). The optimal linear precoder can be computed by means of a fixed- point equation as a function of the channel and the input constellation. We show that diagonalizing the channel matrix does not maximize the information transmission rate for nonGaussian inputs. A full precoding matrix may significantly increase the information transmission rate, even for parallel non-interacting channels. We illustrate the application of our results to typical Gigabit DSL systems.},
keywords = {Bit error rate, channel matrix diagonalization, Communications Society, Computer science, digital subscriber lines, DSL, Equations, fixed-point equation, Gaussian channels, least mean squares methods, linear codes, matrix algebra, MIMO, MIMO communication, MIMO Gaussian channel, minimum mean squared error method, MMSE, multiple-input multiple-output communication, Mutual information, optimal linear precoder, precoding, Telecommunications, Telephony},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarWe determine the linear precoding policy that maximizes the mutual information for general multiple-input multiple-output (MIMO) Gaussian channels with arbitrary input distributions, by capitalizing on the relationship between mutual information and minimum mean squared error (MMSE). The optimal linear precoder can be computed by means of a fixed- point equation as a function of the channel and the input constellation. We show that diagonalizing the channel matrix does not maximize the information transmission rate for nonGaussian inputs. A full precoding matrix may significantly increase the information transmission rate, even for parallel non-interacting channels. We illustrate the application of our results to typical Gigabit DSL systems.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4533270Cerrar Koch, Tobias;  Lapidoth, AmosMultipath Channels of Bounded Capacity Artículo en actas En: 2008 IEEE Information Theory Workshop, pp. 6–10, IEEE, Oporto, 2008, ISBN: 978-1-4244-2269-2.Resumen | Enlaces | BibTeX | Etiquetas: @inproceedings{Koch2008a,
title = {Multipath Channels of Bounded Capacity},
author = {Tobias Koch and Amos Lapidoth},
url = {http://www.researchgate.net/publication/4353168_Multipath_channels_of_bounded_capacity},
isbn = {978-1-4244-2269-2},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 IEEE Information Theory Workshop},
pages = {6--10},
publisher = {IEEE},
address = {Oporto},
abstract = {The capacity of discrete-time, non-coherent, multi-path fading channels is considered. It is shown that if the delay spread is large in the sense that the variances of the path gains do not decay faster than geometrically, then capacity is bounded in the signal-to-noise ratio.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarThe capacity of discrete-time, non-coherent, multi-path fading channels is considered. It is shown that if the delay spread is large in the sense that the variances of the path gains do not decay faster than geometrically, then capacity is bounded in the signal-to-noise ratio.Cerrarhttp://www.researchgate.net/publication/4353168_Multipath_channels_of_bounded_ca[...]Cerrar Leiva-murillo, Jose M;  Artés-Rodríguez, AntonioLinear Dimensionality Reduction With Gausian Mixture Models Artículo en actas En: Cognitive Information Processing, (CIP) 2008, Santorini, 2008.Resumen | Enlaces | BibTeX | Etiquetas: @inproceedings{JoseM.Leiva-murillo2008,
title = {Linear Dimensionality Reduction With Gausian Mixture Models},
author = {Jose M Leiva-murillo and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.798},
year  = {2008},
date = {2008-01-01},
booktitle = {Cognitive Information Processing, (CIP) 2008},
address = {Santorini},
abstract = {In this paper, we explore the application of several informationtheoretic criteria to the problem of reducing the dimension in pattern recognition. We consider the use of Gaussian mixture models for estimating the distribution of the data. Three algorithms are proposed for linear feature extraction by the maximization of the mutual information, the likelihood or the hypotheses test, respectively. The experiments show that the proposed methods outperform the classical methods based on parametric Gaussian models, and avoid the intense computational complexity of nonparametric kernel density estimators.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarIn this paper, we explore the application of several informationtheoretic criteria to the problem of reducing the dimension in pattern recognition. We consider the use of Gaussian mixture models for estimating the distribution of the data. Three algorithms are proposed for linear feature extraction by the maximization of the mutual information, the likelihood or the hypotheses test, respectively. The experiments show that the proposed methods outperform the classical methods based on parametric Gaussian models, and avoid the intense computational complexity of nonparametric kernel density estimators.Cerrarhttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.798Cerrar Koch, Tobias;  Lapidoth, AmosMultipath Channels of Unbounded Capacity Artículo en actas En: 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, pp. 640–644, IEEE, Eilat, 2008, ISBN: 978-1-4244-2481-8.Resumen | Enlaces | BibTeX | Etiquetas: channel capacity, discrete-time capacity, Entropy, Fading, fading channels, Frequency, H infinity control, Information rates, multipath channels, multipath fading channels, noncoherent, noncoherent capacity, path gains decay, Signal to noise ratio, statistics, Transmitters, unbounded capacity@inproceedings{Koch2008b,
title = {Multipath Channels of Unbounded Capacity},
author = {Tobias Koch and Amos Lapidoth},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4736611},
isbn = {978-1-4244-2481-8},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel},
pages = {640--644},
publisher = {IEEE},
address = {Eilat},
abstract = {The capacity of discrete-time, noncoherent, multipath fading channels is considered. It is shown that if the variances of the path gains decay faster than exponentially, then capacity is unbounded in the transmit power.},
keywords = {channel capacity, discrete-time capacity, Entropy, Fading, fading channels, Frequency, H infinity control, Information rates, multipath channels, multipath fading channels, noncoherent, noncoherent capacity, path gains decay, Signal to noise ratio, statistics, Transmitters, unbounded capacity},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarThe capacity of discrete-time, noncoherent, multipath fading channels is considered. It is shown that if the variances of the path gains decay faster than exponentially, then capacity is unbounded in the transmit power.Cerrarhttp://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4736611Cerrar Rodrigues, Miguel R D;  Perez-Cruz, Fernando;  Verdu, SergioMultiple-Input Multiple-Output Gaussian Channels: Optimal Covariance for Non-Gaussian Inputs Artículo en actas En: 2008 IEEE Information Theory Workshop, pp. 445–449, IEEE, Porto, 2008, ISBN: 978-1-4244-2269-2.Resumen | Enlaces | BibTeX | Etiquetas: Binary phase shift keying, covariance matrices, Covariance matrix, deterministic MIMO Gaussian channel, fixed-point equation, Gaussian channels, Gaussian noise, Information rates, intersymbol interference, least mean squares methods, Magnetic recording, mercury-waterfilling power allocation policy, MIMO, MIMO communication, minimum mean-squared error, MMSE, MMSE matrix, multiple-input multiple-output system, Multiple-Input Multiple-Output Systems, Mutual information, Optimal Input Covariance, Optimization, Telecommunications@inproceedings{Rodrigues2008,
title = {Multiple-Input Multiple-Output Gaussian Channels: Optimal Covariance for Non-Gaussian Inputs},
author = {Miguel R D Rodrigues and Fernando Perez-Cruz and Sergio Verdu},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4578704},
isbn = {978-1-4244-2269-2},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 IEEE Information Theory Workshop},
pages = {445--449},
publisher = {IEEE},
address = {Porto},
abstract = {We investigate the input covariance that maximizes the mutual information of deterministic multiple-input multipleo-utput (MIMO) Gaussian channels with arbitrary (not necessarily Gaussian) input distributions, by capitalizing on the relationship between the gradient of the mutual information and the minimum mean-squared error (MMSE) matrix. We show that the optimal input covariance satisfies a simple fixed-point equation involving key system quantities, including the MMSE matrix. We also specialize the form of the optimal input covariance to the asymptotic regimes of low and high snr. We demonstrate that in the low-snr regime the optimal covariance fully correlates the inputs to better combat noise. In contrast, in the high-snr regime the optimal covariance is diagonal with diagonal elements obeying the generalized mercury/waterfilling power allocation policy. Numerical results illustrate that covariance optimization may lead to significant gains with respect to conventional strategies based on channel diagonalization followed by mercury/waterfilling or waterfilling power allocation, particularly in the regimes of medium and high snr.},
keywords = {Binary phase shift keying, covariance matrices, Covariance matrix, deterministic MIMO Gaussian channel, fixed-point equation, Gaussian channels, Gaussian noise, Information rates, intersymbol interference, least mean squares methods, Magnetic recording, mercury-waterfilling power allocation policy, MIMO, MIMO communication, minimum mean-squared error, MMSE, MMSE matrix, multiple-input multiple-output system, Multiple-Input Multiple-Output Systems, Mutual information, Optimal Input Covariance, Optimization, Telecommunications},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarWe investigate the input covariance that maximizes the mutual information of deterministic multiple-input multipleo-utput (MIMO) Gaussian channels with arbitrary (not necessarily Gaussian) input distributions, by capitalizing on the relationship between the gradient of the mutual information and the minimum mean-squared error (MMSE) matrix. We show that the optimal input covariance satisfies a simple fixed-point equation involving key system quantities, including the MMSE matrix. We also specialize the form of the optimal input covariance to the asymptotic regimes of low and high snr. We demonstrate that in the low-snr regime the optimal covariance fully correlates the inputs to better combat noise. In contrast, in the high-snr regime the optimal covariance is diagonal with diagonal elements obeying the generalized mercury/waterfilling power allocation policy. Numerical results illustrate that covariance optimization may lead to significant gains with respect to conventional strategies based on channel diagonalization followed by mercury/waterfilling or waterfilling power allocation, particularly in the regimes of medium and high snr.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4578704Cerrar Vazquez, Manuel A;  Miguez, JoaquinA Per-Survivor Processing Algorithm for Maximum Likelihood Equalization of MIMO Channels with Unknown Order Artículo en actas En: 2008 International ITG Workshop on Smart Antennas, pp. 387–391, IEEE, Vienna, 2008, ISBN: 978-1-4244-1756-8.Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, channel impulse response, computational complexity, Computer science education, Computer Simulation, Degradation, Frequency, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood equalization, maximum likelihood estimation, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channels, MIMO communication, per-survivor processing algorithm, time-selective channels, Transmitting antennas@inproceedings{Vazquez2008a,
title = {A Per-Survivor Processing Algorithm for Maximum Likelihood Equalization of MIMO Channels with Unknown Order},
author = {Manuel A Vazquez and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4475587},
isbn = {978-1-4244-1756-8},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 International ITG Workshop on Smart Antennas},
pages = {387--391},
publisher = {IEEE},
address = {Vienna},
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 possibly means overestimating the channel order, and is not desirable since the computational complexity of maximum likelihood sequence detection (MLSD) in frequency-selective channels grows exponentially with the channel order. In addition to that, the higher the channel order considered, the more the number of channel coefficients that need to be estimated from the same set of observations. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. 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 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 = {Channel estimation, channel impulse response, computational complexity, Computer science education, Computer Simulation, Degradation, Frequency, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood equalization, maximum likelihood estimation, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channels, MIMO communication, per-survivor processing algorithm, time-selective channels, Transmitting antennas},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarIn 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 possibly means overestimating the channel order, and is not desirable since the computational complexity of maximum likelihood sequence detection (MLSD) in frequency-selective channels grows exponentially with the channel order. In addition to that, the higher the channel order considered, the more the number of channel coefficients that need to be estimated from the same set of observations. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. 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 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.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4475587Cerrar Leiva-Murillo, Jose M;  Artés-Rodríguez, AntonioAlgorithms for Gaussian Bandwidth Selection in Kernel Density Estimators Artículo en actas En: NIPS 2008, Workshop on Optimization for Machine Learning Vancouver, Vancouver, 2008.Resumen | Enlaces | BibTeX | Etiquetas: @inproceedings{Leiva-Murillo2008a,
title = {Algorithms for Gaussian Bandwidth Selection in Kernel Density Estimators},
author = {Jose M Leiva-Murillo and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.researchgate.net/publication/228859873_Algorithms_for_gaussian_bandwidth_selection_in_kernel_density_estimators},
year  = {2008},
date = {2008-01-01},
booktitle = {NIPS 2008, Workshop on Optimization for Machine Learning Vancouver},
address = {Vancouver},
abstract = {In this paper we study the classical statistical problem of choos-ing an appropriate bandwidth for Kernel Density Estimators. For the special case of Gaussian kernel, two algorithms are proposed for the spherical covariance matrix and for the general case, respec-tively. These methods avoid the unsatisfactory procedure of tuning the bandwidth while evaluating the likelihood, which is impractical with multivariate data in the general case. The convergence con-ditions are provided together with the algorithms proposed. We measure the accuracy of the models obtained by a set of classifica-tion experiments.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarIn this paper we study the classical statistical problem of choos-ing an appropriate bandwidth for Kernel Density Estimators. For the special case of Gaussian kernel, two algorithms are proposed for the spherical covariance matrix and for the general case, respec-tively. These methods avoid the unsatisfactory procedure of tuning the bandwidth while evaluating the likelihood, which is impractical with multivariate data in the general case. The convergence con-ditions are provided together with the algorithms proposed. We measure the accuracy of the models obtained by a set of classifica-tion experiments.Cerrarhttp://www.researchgate.net/publication/228859873_Algorithms_for_gaussian_bandwi[...]Cerrar de-Prado-Cumplido, Mario Mario;  Artés-Rodríguez, AntonioSVM Discovery of Causation Direction by Machine Learning Techniques Artículo en actas En: NIPS’08, Workshop on Causality, Vancouver, 2008.BibTeX | Etiquetas: @inproceedings{Mariode-Prado-Cumplido2008,
title = {SVM Discovery of Causation Direction by Machine Learning Techniques},
author = {Mario Mario de-Prado-Cumplido and Antonio Art\'{e}s-Rodr\'{i}guez},
year  = {2008},
date = {2008-01-01},
booktitle = {NIPS’08, Workshop on Causality},
address = {Vancouver},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrar Ruiz, Manuel Martinez;  Artés-Rodríguez, Antonio;  Sabatini, RProgressive Still Image Transmission over a Tactical Data Link Network Artículo en actas En: RTO 2008 Information Systems Technology Panel (IST) Symposium, Praga, 2008.Resumen | BibTeX | Etiquetas: @inproceedings{MartinezRuiz2008,
title = {Progressive Still Image Transmission over a Tactical Data Link Network},
author = {Manuel Martinez Ruiz and Antonio Art\'{e}s-Rodr\'{i}guez and R Sabatini},
year  = {2008},
date = {2008-01-01},
booktitle = {RTO 2008 Information Systems Technology Panel (IST) Symposium},
address = {Praga},
abstract = {Future military communications will be required to provide higher data capacity and wideband in real time, greater flexibility, reliability, robustness and seamless networking capabilities. The next generation of communication systems and standards should be able to outperform in a littoral combat environment with a high density of civilian emissions and “ad-hoc” spot jammers. In this operational context it is extremely important to ensure the proper performance of the information grid and to provide not all the available but only the required information in real time either by broadcasting or upon demand, with the best possible “quality of service”. Existing tactical data link systems and standards have being designed to convey mainly textual information such as surveillance and identification data, electronic warfare parameters, aircraft control information, coded voice. The future tactical data link systems and standards should take into consideration the multimedia nature of most of the dispersed and “fuzzy” information available in the battlefield to correlate the ISR components in a way to better contribute to the Network Centric Operations. For this to be accomplished new wideband coalition waveforms should be developed and new coding and image compression standards should be taken into account, such as MPEG-7 (Multimedia Content Description Interface), MPEG-21, JPEG2000 and many others. In the meantime it is important to find new applications for the current tactical data links in order to better exploit their capabilities and to overcome or minimize their limitations.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarFuture military communications will be required to provide higher data capacity and wideband in real time, greater flexibility, reliability, robustness and seamless networking capabilities. The next generation of communication systems and standards should be able to outperform in a littoral combat environment with a high density of civilian emissions and “ad-hoc” spot jammers. In this operational context it is extremely important to ensure the proper performance of the information grid and to provide not all the available but only the required information in real time either by broadcasting or upon demand, with the best possible “quality of service”. Existing tactical data link systems and standards have being designed to convey mainly textual information such as surveillance and identification data, electronic warfare parameters, aircraft control information, coded voice. The future tactical data link systems and standards should take into consideration the multimedia nature of most of the dispersed and “fuzzy” information available in the battlefield to correlate the ISR components in a way to better contribute to the Network Centric Operations. For this to be accomplished new wideband coalition waveforms should be developed and new coding and image compression standards should be taken into account, such as MPEG-7 (Multimedia Content Description Interface), MPEG-21, JPEG2000 and many others. In the meantime it is important to find new applications for the current tactical data links in order to better exploit their capabilities and to overcome or minimize their limitations.Cerrar Bravo-Santos, Ángel MMultireception Systems in Mobile Environments Artículo en actas En: 2008 International Workshop on Advances in Communications, Victoria BC, 2008.BibTeX | Etiquetas: @inproceedings{Bravo-Santos2008,
title = {Multireception Systems in Mobile Environments},
author = {\'{A}ngel M Bravo-Santos},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 International Workshop on Advances in Communications},
address = {Victoria BC},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrar Plata-Chaves, Jorge;  Lázaro, Marcelino;  Artés-Rodríguez, AntonioDecentralized Detection in a Dense Wireless Sensor Network with Correlated Observations Artículo en actas En: International Workshop on Information Theory for Sensor Networks (WITS 2008), Santorini, 2008.Enlaces | BibTeX | Etiquetas: @inproceedings{Plata-Chaves2008,
title = {Decentralized Detection in a Dense Wireless Sensor Network with Correlated Observations},
author = {Jorge Plata-Chaves and Marcelino L\'{a}zaro and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.dcc.fc.up.pt/wits08/wits-advance-program.pdf},
year  = {2008},
date = {2008-01-01},
booktitle = {International Workshop on Information Theory for Sensor Networks (WITS 2008)},
address = {Santorini},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrarhttp://www.dcc.fc.up.pt/wits08/wits-advance-program.pdfCerrar Santiago-Mozos, Ricardo;  Fernandez-Lorenzana, R;  Perez-Cruz, Fernando;  Artés-Rodríguez, AntonioOn the Uncertainty in Sequential Hypothesis Testing Artículo en actas En: 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 1223–1226, IEEE, Paris, 2008, ISBN: 978-1-4244-2002-5.Resumen | Enlaces | BibTeX | Etiquetas: binary hypothesis test, Biomedical imaging, Detectors, H infinity control, likelihood ratio, Medical diagnostic imaging, medical image application, medical image processing, Medical tests, patient diagnosis, Probability, Random variables, Sequential analysis, sequential hypothesis testing, sequential probability ratio test, Signal processing, Testing, tuberculosis diagnosis, Uncertainty@inproceedings{Santiago-Mozos2008,
title = {On the Uncertainty in Sequential Hypothesis Testing},
author = {Ricardo Santiago-Mozos and R Fernandez-Lorenzana and Fernando Perez-Cruz and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4541223},
isbn = {978-1-4244-2002-5},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
pages = {1223--1226},
publisher = {IEEE},
address = {Paris},
abstract = {We consider the problem of sequential hypothesis testing when the exact pdfs are not known but instead a set of iid samples are used to describe the hypotheses. We modify the classical test by introducing a likelihood ratio interval which accommodates the uncertainty in the pdfs. The test finishes when the whole likelihood ratio interval crosses one of the thresholds and reduces to the classical test as the number of samples to describe the hypotheses tend to infinity. We illustrate the performance of this test in a medical image application related to tuberculosis diagnosis. We show in this example how the test confidence level can be accurately determined.},
keywords = {binary hypothesis test, Biomedical imaging, Detectors, H infinity control, likelihood ratio, Medical diagnostic imaging, medical image application, medical image processing, Medical tests, patient diagnosis, Probability, Random variables, Sequential analysis, sequential hypothesis testing, sequential probability ratio test, Signal processing, Testing, tuberculosis diagnosis, Uncertainty},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarWe consider the problem of sequential hypothesis testing when the exact pdfs are not known but instead a set of iid samples are used to describe the hypotheses. We modify the classical test by introducing a likelihood ratio interval which accommodates the uncertainty in the pdfs. The test finishes when the whole likelihood ratio interval crosses one of the thresholds and reduces to the classical test as the number of samples to describe the hypotheses tend to infinity. We illustrate the performance of this test in a medical image application related to tuberculosis diagnosis. We show in this example how the test confidence level can be accurately determined.Cerrarhttp://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4541223Cerrar Vila-Forcen, J E;  Artés-Rodríguez, Antonio;  Garcia-Frias, JCompressive Sensing Detection of Stochastic Signals Artículo en actas En: 2008 42nd Annual Conference on Information Sciences and Systems, pp. 956–960, IEEE, Princeton, 2008, ISBN: 978-1-4244-2246-3.Resumen | Enlaces | BibTeX | Etiquetas: Additive white noise, AWGN, compressive sensing detection, dimensionality reduction techniques, Distortion measurement, Gaussian noise, matrix algebra, Mutual information, optimized projections, projection matrix, signal detection, Signal processing, signal reconstruction, Stochastic processes, stochastic signals, Support vector machine classification, Support vector machines, SVM@inproceedings{Vila-Forcen2008,
title = {Compressive Sensing Detection of Stochastic Signals},
author = {J E Vila-Forcen and Antonio Art\'{e}s-Rodr\'{i}guez and J Garcia-Frias},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4558656},
isbn = {978-1-4244-2246-3},
year  = {2008},
date = {2008-01-01},
booktitle = {2008 42nd Annual Conference on Information Sciences and Systems},
pages = {956--960},
publisher = {IEEE},
address = {Princeton},
abstract = {Inspired by recent work in compressive sensing, we propose a framework for the detection of stochastic signals from optimized projections. In order to generate a good projection matrix, we use dimensionality reduction techniques based on the maximization of the mutual information between the projected signals and their corresponding class labels. In addition, classification techniques based on support vector machines (SVMs) are applied for the final decision process. Simulation results show that the realizations of the stochastic process are detected with higher accuracy and lower complexity than a scheme performing signal reconstruction first, followed by detection based on the reconstructed signal.},
keywords = {Additive white noise, AWGN, compressive sensing detection, dimensionality reduction techniques, Distortion measurement, Gaussian noise, matrix algebra, Mutual information, optimized projections, projection matrix, signal detection, Signal processing, signal reconstruction, Stochastic processes, stochastic signals, Support vector machine classification, Support vector machines, SVM},
pubstate = {published},
tppubtype = {inproceedings}
}
CerrarInspired by recent work in compressive sensing, we propose a framework for the detection of stochastic signals from optimized projections. In order to generate a good projection matrix, we use dimensionality reduction techniques based on the maximization of the mutual information between the projected signals and their corresponding class labels. In addition, classification techniques based on support vector machines (SVMs) are applied for the final decision process. Simulation results show that the realizations of the stochastic process are detected with higher accuracy and lower complexity than a scheme performing signal reconstruction first, followed by detection based on the reconstructed signal.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4558656Cerrar Perez-Cruz, FernandoEstimation of Information Theoretic Measures for Continuous Random Variables Artículo en actas En: Advances in Neural Information Processing Systems, pp. 1257–1264, Vancouver, 2008.Enlaces | BibTeX | Etiquetas: @inproceedings{Perez-Cruz2008b,
title = {Estimation of Information Theoretic Measures for Continuous Random Variables},
author = {Fernando Perez-Cruz},
url = {http://papers.nips.cc/paper/3417-estimation-of-information-theoretic-measures-for-continuous-random-variables},
year  = {2008},
date = {2008-01-01},
booktitle = {Advances in Neural Information Processing Systems},
pages = {1257--1264},
address = {Vancouver},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Cerrarhttp://papers.nips.cc/paper/3417-estimation-of-information-theoretic-measures-fo[...]Cerrar Perez-Cruz, Fernando;  Murillo-Fuentes, Juan Jose;  Caro, SNonlinear Channel Equalization With Gaussian Processes for Regression Artículo de revista En: IEEE Transactions on Signal Processing, vol. 56, no. 10, pp. 5283–5286, 2008, ISSN: 1053-587X.Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, digital communications receivers, equalisers, equalization, Gaussian processes, kernel adaline, least mean squares methods, maximum likelihood estimation, nonlinear channel equalization, nonlinear equalization, nonlinear minimum mean square error estimator, regression, regression analysis, short training sequences, Support vector machines@article{Perez-Cruz2008c,
title = {Nonlinear Channel Equalization With Gaussian Processes for Regression},
author = {Fernando Perez-Cruz and Juan Jose Murillo-Fuentes and S Caro},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4563433},
issn = {1053-587X},
year  = {2008},
date = {2008-01-01},
journal = {IEEE Transactions on Signal Processing},
volume = {56},
number = {10},
pages = {5283--5286},
abstract = {We propose Gaussian processes for regression (GPR) as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimation approaches, lies on their capability to optimize the kernel hyperparameters by maximum likelihood, which improves its performance significantly for short training sequences. Besides, GPR can be understood as a nonlinear minimum mean square error estimator, a standard criterion for training equalizers that trades off the inversion of the channel and the amplification of the noise. In the experiment section, we show that the GPR-based equalizer clearly outperforms support vector machine and kernel adaline approaches, exhibiting outstanding results for short training sequences.},
keywords = {Channel estimation, digital communications receivers, equalisers, equalization, Gaussian processes, kernel adaline, least mean squares methods, maximum likelihood estimation, nonlinear channel equalization, nonlinear equalization, nonlinear minimum mean square error estimator, regression, regression analysis, short training sequences, Support vector machines},
pubstate = {published},
tppubtype = {article}
}
CerrarWe propose Gaussian processes for regression (GPR) as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimation approaches, lies on their capability to optimize the kernel hyperparameters by maximum likelihood, which improves its performance significantly for short training sequences. Besides, GPR can be understood as a nonlinear minimum mean square error estimator, a standard criterion for training equalizers that trades off the inversion of the channel and the amplification of the noise. In the experiment section, we show that the GPR-based equalizer clearly outperforms support vector machine and kernel adaline approaches, exhibiting outstanding results for short training sequences.Cerrarhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4563433Cerrar Baca-García, Enrique;  Perez-Rodriguez, Mercedes M;  Basurte-Villamor, Ignacio;  Quintero-Gutierrez, Javier F;  Sevilla-Vicente, Juncal;  Martinez-Vigo, Maria;  Artés-Rodríguez, Antonio; del Moral, Antonio Fernandez L;  Jimenez-Arriero, Miguel A; de Rivera, Jose Gonzalez LPatterns of Mental Health Service Utilization in a General Hospital and Outpatient Mental Health Facilities: Analysis of 365,262 Psychiatric Consultations Artículo de revista En: European archives of psychiatry and clinical neuroscience, vol. 258, no. 2, pp. 117–123, 2008, ISSN: 0940-1334.Resumen | Enlaces | BibTeX | Etiquetas: 80 and over, Adolescent, Adult, Age Distribution, Aged, Ambulatory Care, Ambulatory Care: statistics &amp;amp; numerical data, Ambulatory Care: utilization, Child, Diagnosis-Related Groups, Female, General, General: statistics &amp;amp; numerical data, General: utilization, Health Care Costs, Health Care Costs: statistics &amp;amp; numerical data, Health Services Accessibility, Health Services Accessibility: statistics &amp;amp; numeri, Health Services Needs and Demand, Health Services Needs and Demand: statistics &amp;amp; num, Hospitals, Humans, Male, Mental Disorders, Mental Disorders: classification, Mental Disorders: diagnosis, Mental Disorders: epidemiology, Mental Disorders: therapy, Mental Health Services, Mental Health Services: economics, Mental Health Services: utilization, Middle Aged, Outcome and Process Assessment (Health Care), Preschool, Psychiatry, Psychiatry: economics, Psychiatry: statistics &amp;amp; numerical data, Sex Distribution, Spain, Spain: epidemiology, Utilization Review, Utilization Review: statistics &amp;amp; numerical data@article{Baca-Garcia2008,
title = {Patterns of Mental Health Service Utilization in a General Hospital and Outpatient Mental Health Facilities: Analysis of 365,262 Psychiatric Consultations},
author = {Enrique Baca-Garc\'{i}a and Mercedes M Perez-Rodriguez and Ignacio Basurte-Villamor and Javier F Quintero-Gutierrez and Juncal Sevilla-Vicente and Maria Martinez-Vigo and Antonio Art\'{e}s-Rodr\'{i}guez and Antonio Fernandez L del Moral and Miguel A Jimenez-Arriero and Jose Gonzalez L de Rivera},
url = {http://www.ncbi.nlm.nih.gov/pubmed/17990050},
issn = {0940-1334},
year  = {2008},
date = {2008-01-01},
journal = {European archives of psychiatry and clinical neuroscience},
volume = {258},
number = {2},
pages = {117--123},
abstract = {PURPOSE: Mental health is one of the priorities of the European Commission. Studies of the use and cost of mental health facilities are needed in order to improve the planning and efficiey of mental health resources. We analyze the patterns of mental health service use in multiple clinical settings to identify factors associated with high cost. SUBJECTS AND METHODS: 22,859 patients received psychiatric care in the catchment area of a Spanish hospital (2000-2004). They had 365,262 psychiatric consultations in multiple settings. Two groups were selected that generated 80% of total costs: the medium cost group (N = 4,212; 50% of costs), and the high cost group (N = 236; 30% of costs). Statistical analyses were performed using univariate and multivariate techniques. Significant variables in univariate analyses were introduced as independent variables in a logistic regression analysis using "high cost" (>7,263$) as dependent variable. RESULTS: Costs were not evenly distributed throughout the sample. 19.4% of patients generated 80% of costs. The variables associated with high cost were: age group 1 (0-14 years) at the first evaluation, permanent disability, and ICD-10 diagnoses: Organic, including symptomatic, mental disorders; Mental and behavioural disorders due to psychoactive substance use; Schizophrenia, schizotypal and delusional disorders; Behavioural syndromes associated with physiological disturbances and physical factors; External causes of morbidity and mortality; and Factors influencing health status and contact with health services. DISCUSSION: Mental healthcare costs were not evenly distributed throughout the patient population. The highest costs are associated with early onset of the mental disorder, permanent disability, organic mental disorders, substance-related disorders, psychotic disorders, and external factors that influence the health status and contact with health services or cause morbidity and mortality. CONCLUSION: Variables related to psychiatric diagnoses and sociodemographic factors have influence on the cost of mental healthcare.},
keywords = {80 and over, Adolescent, Adult, Age Distribution, Aged, Ambulatory Care, Ambulatory Care: statistics \&amp;amp; numerical data, Ambulatory Care: utilization, Child, Diagnosis-Related Groups, Female, General, General: statistics \&amp;amp; numerical data, General: utilization, Health Care Costs, Health Care Costs: statistics \&amp;amp; numerical data, Health Services Accessibility, Health Services Accessibility: statistics \&amp;amp; numeri, Health Services Needs and Demand, Health Services Needs and Demand: statistics \&amp;amp; num, Hospitals, Humans, Male, Mental Disorders, Mental Disorders: classification, Mental Disorders: diagnosis, Mental Disorders: epidemiology, Mental Disorders: therapy, Mental Health Services, Mental Health Services: economics, Mental Health Services: utilization, Middle Aged, Outcome and Process Assessment (Health Care), Preschool, Psychiatry, Psychiatry: economics, Psychiatry: statistics \&amp;amp; numerical data, Sex Distribution, Spain, Spain: epidemiology, Utilization Review, Utilization Review: statistics \&amp;amp; numerical data},
pubstate = {published},
tppubtype = {article}
}
CerrarPURPOSE: Mental health is one of the priorities of the European Commission. Studies of the use and cost of mental health facilities are needed in order to improve the planning and efficiey of mental health resources. We analyze the patterns of mental health service use in multiple clinical settings to identify factors associated with high cost. SUBJECTS AND METHODS: 22,859 patients received psychiatric care in the catchment area of a Spanish hospital (2000-2004). They had 365,262 psychiatric consultations in multiple settings. Two groups were selected that generated 80% of total costs: the medium cost group (N = 4,212; 50% of costs), and the high cost group (N = 236; 30% of costs). Statistical analyses were performed using univariate and multivariate techniques. Significant variables in univariate analyses were introduced as independent variables in a logistic regression analysis using "high cost" (>7,263$) as dependent variable. RESULTS: Costs were not evenly distributed throughout the sample. 19.4% of patients generated 80% of costs. The variables associated with high cost were: age group 1 (0-14 years) at the first evaluation, permanent disability, and ICD-10 diagnoses: Organic, including symptomatic, mental disorders; Mental and behavioural disorders due to psychoactive substance use; Schizophrenia, schizotypal and delusional disorders; Behavioural syndromes associated with physiological disturbances and physical factors; External causes of morbidity and mortality; and Factors influencing health status and contact with health services. DISCUSSION: Mental healthcare costs were not evenly distributed throughout the patient population. The highest costs are associated with early onset of the mental disorder, permanent disability, organic mental disorders, substance-related disorders, psychotic disorders, and external factors that influence the health status and contact with health services or cause morbidity and mortality. CONCLUSION: Variables related to psychiatric diagnoses and sociodemographic factors have influence on the cost of mental healthcare.Cerrarhttp://www.ncbi.nlm.nih.gov/pubmed/17990050Cerrar Perez-Cruz, Fernando;  Murillo-Fuentes, Juan JoseDigital Communication Receivers Using Gaussian Processes for Machine Learning Artículo de revista En: EURASIP Journal on Advances in Signal Processing, vol. 2008, no. 1, pp. 1–13, 2008, ISSN: 1687-6172.Resumen | Enlaces | BibTeX | Etiquetas: @article{Perez-Cruz2008d,
title = {Digital Communication Receivers Using Gaussian Processes for Machine Learning},
author = {Fernando Perez-Cruz and Juan Jose Murillo-Fuentes},
url = {http://asp.eurasipjournals.com/content/2008/1/491503},
issn = {1687-6172},
year  = {2008},
date = {2008-01-01},
journal = {EURASIP Journal on Advances in Signal Processing},
volume = {2008},
number = {1},
pages = {1--13},
publisher = {Springer},
abstract = {We propose Gaussian processes (GPs) as a novel nonlinear receiver for digital communication systems. The GPs framework can be used to solve both classification (GPC) and regression (GPR) problems. The minimum mean squared error solution is the expectation of the transmitted symbol given the information at the receiver, which is a nonlinear function of the received symbols for discrete inputs. GPR can be presented as a nonlinear MMSE estimator and thus capable of achieving optimal performance from MMSE viewpoint. Also, the design of digital communication receivers can be viewed as a detection problem, for which GPC is specially suited as it assigns posterior probabilities to each transmitted symbol. We explore the suitability of GPs as nonlinear digital communication receivers. GPs are Bayesian machine learning tools that formulates a likelihood function for its hyperparameters, which can then be set optimally. GPs outperform state-of-the-art nonlinear machine learning approaches that prespecify their hyperparameters or rely on cross validation. We illustrate the advantages of GPs as digital communication receivers for linear and nonlinear channel models for short training sequences and compare them to state-of-the-art nonlinear machine learning tools, such as support vector machines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
CerrarWe propose Gaussian processes (GPs) as a novel nonlinear receiver for digital communication systems. The GPs framework can be used to solve both classification (GPC) and regression (GPR) problems. The minimum mean squared error solution is the expectation of the transmitted symbol given the information at the receiver, which is a nonlinear function of the received symbols for discrete inputs. GPR can be presented as a nonlinear MMSE estimator and thus capable of achieving optimal performance from MMSE viewpoint. Also, the design of digital communication receivers can be viewed as a detection problem, for which GPC is specially suited as it assigns posterior probabilities to each transmitted symbol. We explore the suitability of GPs as nonlinear digital communication receivers. GPs are Bayesian machine learning tools that formulates a likelihood function for its hyperparameters, which can then be set optimally. GPs outperform state-of-the-art nonlinear machine learning approaches that prespecify their hyperparameters or rely on cross validation. We illustrate the advantages of GPs as digital communication receivers for linear and nonlinear channel models for short training sequences and compare them to state-of-the-art nonlinear machine learning tools, such as support vector machines.Cerrarhttp://asp.eurasipjournals.com/content/2008/1/491503Cerrar Leiva-Murillo, Jose M;  Salcedo-Sanz, Sancho;  Gallardo-Antolín, Ascensión;  Artés-Rodríguez, AntonioA Simulated Annealing Approach to Speaker Segmentation in Audio Databases Artículo de revista En: Engineering Applications of Artificial Intelligence, vol. 21, no. 4, pp. 499–508, 2008.Resumen | Enlaces | BibTeX | Etiquetas: Audio indexing, information theory, Simulated annealing, Speaker segmentation@article{Leiva-Murillo2008c,
title = {A Simulated Annealing Approach to Speaker Segmentation in Audio Databases},
author = {Jose M Leiva-Murillo and Sancho Salcedo-Sanz and Ascensi\'{o}n Gallardo-Antol\'{i}n and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.sciencedirect.com/science/article/pii/S0952197607000954},
year  = {2008},
date = {2008-01-01},
journal = {Engineering Applications of Artificial Intelligence},
volume = {21},
number = {4},
pages = {499--508},
abstract = {In this paper we present a novel approach to the problem of speaker segmentation, which is an unavoidable previous step to audio indexing. Mutual information is used for evaluating the accuracy of the segmentation, as a function to be maximized by a simulated annealing (SA) algorithm. We introduce a novel mutation operator for the SA, the Consecutive Bits Mutation operator, which improves the performance of the SA in this problem. We also use the so-called Compaction Factor, which allows the SA to operate in a reduced search space. Our algorithm has been tested in the segmentation of real audio databases, and it has been compared to several existing algorithms for speaker segmentation, obtaining very good results in the test problems considered.},
keywords = {Audio indexing, information theory, Simulated annealing, Speaker segmentation},
pubstate = {published},
tppubtype = {article}
}
CerrarIn this paper we present a novel approach to the problem of speaker segmentation, which is an unavoidable previous step to audio indexing. Mutual information is used for evaluating the accuracy of the segmentation, as a function to be maximized by a simulated annealing (SA) algorithm. We introduce a novel mutation operator for the SA, the Consecutive Bits Mutation operator, which improves the performance of the SA in this problem. We also use the so-called Compaction Factor, which allows the SA to operate in a reduced search space. Our algorithm has been tested in the segmentation of real audio databases, and it has been compared to several existing algorithms for speaker segmentation, obtaining very good results in the test problems considered.Cerrarhttp://www.sciencedirect.com/science/article/pii/S0952197607000954Cerrar Vazquez, Manuel A;  Bugallo, Monica F;  Miguez, JoaquinSequential Monte Carlo Methods for Complexity-Constrained MAP Equalization of Dispersive MIMO Channels Artículo de revista En: Signal Processing, vol. 88, no. 4, pp. 1017–1034, 2008.Resumen | Enlaces | BibTeX | Etiquetas: joint channel and data estimation, Multiple Input Multiple Output (MIMO), Sequential Monte Carlo (SMC)@article{Vazquez2008b,
title = {Sequential Monte Carlo Methods for Complexity-Constrained MAP Equalization of Dispersive MIMO Channels},
author = {Manuel A Vazquez and Monica F Bugallo and Joaquin Miguez},
url = {http://www.sciencedirect.com/science/article/pii/S0165168407003763},
year  = {2008},
date = {2008-01-01},
journal = {Signal Processing},
volume = {88},
number = {4},
pages = {1017--1034},
abstract = {The ability to perform nearly optimal equalization of multiple input multiple output (MIMO) wireless channels using sequential Monte Carlo (SMC) techniques has recently been demonstrated. SMC methods allow to recursively approximate the a posteriori probabilities of the transmitted symbols, as observations are sequentially collected, using samples from adequate probability distributions. Hence, they are a class of online (adaptive) algorithms, suitable to handle the time-varying channels typical of high speed mobile communication applications. The main drawback of the SMC-based MIMO-channel equalizers so far proposed is that their computational complexity grows exponentially with the number of input data streams and the length of the channel impulse response, rendering these methods impractical. In this paper, we introduce novel SMC schemes that overcome this limitation by the adequate design of proposal probability distribution functions that can be sampled with a lesser computational burden, yet provide a close-to-optimal performance in terms of the resulting equalizer bit error rate and channel estimation error. We show that the complexity of the resulting receivers grows polynomially with the number of input data streams and the length of the channel response, and present computer simulation results that illustrate their performance in some typical scenarios.},
keywords = {joint channel and data estimation, Multiple Input Multiple Output (MIMO), Sequential Monte Carlo (SMC)},
pubstate = {published},
tppubtype = {article}
}
CerrarThe ability to perform nearly optimal equalization of multiple input multiple output (MIMO) wireless channels using sequential Monte Carlo (SMC) techniques has recently been demonstrated. SMC methods allow to recursively approximate the a posteriori probabilities of the transmitted symbols, as observations are sequentially collected, using samples from adequate probability distributions. Hence, they are a class of online (adaptive) algorithms, suitable to handle the time-varying channels typical of high speed mobile communication applications. The main drawback of the SMC-based MIMO-channel equalizers so far proposed is that their computational complexity grows exponentially with the number of input data streams and the length of the channel impulse response, rendering these methods impractical. In this paper, we introduce novel SMC schemes that overcome this limitation by the adequate design of proposal probability distribution functions that can be sampled with a lesser computational burden, yet provide a close-to-optimal performance in terms of the resulting equalizer bit error rate and channel estimation error. We show that the complexity of the resulting receivers grows polynomially with the number of input data streams and the length of the channel response, and present computer simulation results that illustrate their performance in some typical scenarios.Cerrarhttp://www.sciencedirect.com/science/article/pii/S0165168407003763Cerrar2007 Leiva-Murillo, Jose M;  Artés-Rodríguez, AntonioMaximization of Mutual Information for Supervised Linear Feature Extraction Artículo de revista En: IEEE Transactions on Neural Networks, vol. 18, no. 5, pp. 1433–1441, 2007, ISSN: 1045-9227.Resumen | Enlaces | BibTeX | Etiquetas: Algorithms, Artificial Intelligence, Automated, component-by-component gradient-ascent method, Computer Simulation, Data Mining, Entropy, Feature extraction, gradient methods, gradient-based entropy, Independent component analysis, Information Storage and Retrieval, information theory, Iron, learning (artificial intelligence), Linear discriminant analysis, Linear Models, Mutual information, Optimization methods, Pattern recognition, Reproducibility of Results, Sensitivity and Specificity, supervised linear feature extraction, Vectors@article{Leiva-Murillo2007,
title = {Maximization of Mutual Information for Supervised Linear Feature Extraction},
author = {Jose M Leiva-Murillo and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4298118},
issn = {1045-9227},
year  = {2007},
date = {2007-01-01},
journal = {IEEE Transactions on Neural Networks},
volume = {18},
number = {5},
pages = {1433--1441},
publisher = {IEEE},
abstract = {In this paper, we present a novel scheme for linear feature extraction in classification. The method is based on the maximization of the mutual information (MI) between the features extracted and the classes. The sum of the MI corresponding to each of the features is taken as an heuristic that approximates the MI of the whole output vector. Then, a component-by-component gradient-ascent method is proposed for the maximization of the MI, similar to the gradient-based entropy optimization used in independent component analysis (ICA). The simulation results show that not only is the method competitive when compared to existing supervised feature extraction methods in all cases studied, but it also remarkably outperform them when the data are characterized by strongly nonlinear boundaries between classes.},
keywords = {Algorithms, Artificial Intelligence, Automated, component-by-component gradient-ascent method, Computer Simulation, Data Mining, Entropy, Feature extraction, gradient methods, gradient-based entropy, Independent component analysis, Information Storage and Retrieval, information theory, Iron, learning (artificial intelligence), Linear discriminant analysis, Linear Models, Mutual information, Optimization methods, Pattern recognition, Reproducibility of Results, Sensitivity and Specificity, supervised linear feature extraction, Vectors},
pubstate = {published},
tppubtype = {article}
}
CerrarIn this paper, we present a novel scheme for linear feature extraction in classification. The method is based on the maximization of the mutual information (MI) between the features extracted and the classes. The sum of the MI corresponding to each of the features is taken as an heuristic that approximates the MI of the whole output vector. Then, a component-by-component gradient-ascent method is proposed for the maximization of the MI, similar to the gradient-based entropy optimization used in independent component analysis (ICA). The simulation results show that not only is the method competitive when compared to existing supervised feature extraction methods in all cases studied, but it also remarkably outperform them when the data are characterized by strongly nonlinear boundaries between classes.Cerrarhttp://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4298118Cerrar0000 Pradier, Melanie F.;  Hyland, Stephanie L.;  Stark, Stefan G.;  Lehmann, Kjong;  Vogt, Julia E.;  Perez-Cruz, Fernando;  Rätsch, GunnarA Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer Types Artículo de revista En preparaciónEn: En preparación.Enlaces | BibTeX | Etiquetas: Bayesian non parametrics@article{FPerez18c,
title = {A Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer Types},
author = {Melanie F. Pradier and Stephanie L. Hyland and Stefan G. Stark and Kjong Lehmann and Julia E. Vogt and Fernando Perez-Cruz and Gunnar R\"{a}tsch},
doi = {https://doi.org/10.1101/623215},
keywords = {Bayesian non parametrics},
pubstate = {forthcoming},
tppubtype = {article}
}
Cerrardoi:https://doi.org/10.1101/623215Cerrar Mariño, Inés P.;  Pérez-Vieites, Sara;  Míguez, JoaquínParameter Estimation and State Forecasting in Meteorological Models Conferencia BOOK OF ABSTRACTS, 0000, (The 6th International Conference on Complex Networks &
Their Applications. Nov. 29 - Dec. 01, 2017, Lyon (France)).BibTeX | Etiquetas: @conference{nokey,
title = {Parameter Estimation and State Forecasting in Meteorological Models},
author = {In\'{e}s P. Mari\~{n}o and Sara P\'{e}rez-Vieites and Joaqu\'{i}n M\'{i}guez},
booktitle = {BOOK OF ABSTRACTS},
pages = {178},
note = {The 6th International Conference on Complex Networks \&
Their Applications. Nov. 29 - Dec. 01, 2017, Lyon (France)},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Cerrar548 registros « ‹ 11 de 11 › » 
 
 
			


				
			
		
	

	

	

	



	
		Login
		
		
			Username
			
		
		
			Password
			
		
		 Remember Me
		
			
			
			
		
		Lost your password?
			
			
			
		
	
		Reset Password
		
		
			Username or E-mail:
			
		
		
			
			
		
		
			Log in
		
		
		
	









$