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2012

Journal Articles

Salamanca, Luis ; Murillo-Fuentes, Juan Jose ; Perez-Cruz, Fernando

Bayesian Equalization for LDPC Channel Decoding Journal Article

IEEE Transactions on Signal Processing, 60 (5), pp. 2672–2676, 2012, ISSN: 1053-587X.

Abstract | Links | BibTeX | Tags: Approximation methods, Bayes methods, Bayesian equalization, Bayesian estimation problem, Bayesian inference, Bayesian methods, BCJR (Bahl–Cocke–Jelinek–Raviv) algorithm, BCJR algorithm, Channel Coding, channel decoding, channel equalization, channel equalization problem, Channel estimation, channel state information, CSI, Decoding, equalisers, Equalizers, expectation propagation, expectation propagation algorithm, fading channels, graphical model representation, intersymbol interference, Kullback-Leibler divergence, LDPC, LDPC coding, low-density parity-check decoder, Modulation, parity check codes, symbol posterior estimates, Training

2011

Inproceedings

Plata-Chaves, Jorge ; Lazaro, M; Artés-Rodríguez, Antonio

Optimal Neyman-Pearson Fusion in Two-Dimensional Densor Networks with Serial Architecture and Dependent Observations Inproceedings

Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on, pp. 1–6, Chicago, 2011, ISBN: 978-1-4577-0267-9.

Abstract | Links | BibTeX | Tags: Bayesian methods, binary distributed detection problem, decision theory, dependent observations, Joints, local decision rule, Measurement uncertainty, Network topology, Neyman-Pearson criterion, optimal Neyman-Pearson fusion, optimum distributed detection, Parallel architectures, Performance evaluation, Probability density function, sensor dependent observations, sensor fusion, serial architecture, serial network topology, two-dimensional sensor networks, Wireless Sensor Networks

2010

Inproceedings

Salamanca, Luis ; Jose Murillo-Fuentes, Juan ; Perez-Cruz, Fernando

Bayesian BCJR for Channel Equalization and Decoding Inproceedings

2010 IEEE International Workshop on Machine Learning for Signal Processing, pp. 53–58, IEEE, Kittila, 2010, ISSN: 1551-2541.

Abstract | Links | BibTeX | Tags: a posteriori probability, Bayes methods, Bayesian BCJR, Bayesian methods, Bit error rate, channel decoding, channel estate information, Channel estimation, Decoding, digital communication, digital communications, equalisers, Equalizers, error statistics, Markov processes, Maximum likelihood decoding, maximum likelihood estimation, multipath channel, probabilistic channel equalization, Probability, single input single output model, SISO model, statistical information, Training

Vinuelas-Peris, Pablo ; Artés-Rodríguez, Antonio

Bayesian Joint Recovery of Correlated Signals in Distributed Compressed Sensing Inproceedings

2010 2nd International Workshop on Cognitive Information Processing, pp. 382–387, IEEE, Elba, 2010, ISBN: 978-1-4244-6459-3.

Abstract | Links | BibTeX | Tags: Bayes methods, Bayesian joint recovery, Bayesian methods, correlated signal, Correlation, correlation methods, Covariance matrix, Dictionaries, distributed compressed sensing, matrix decomposition, Noise measurement, sensors, sparse component correlation coefficient

Salamanca, Luis ; Murillo-Fuentes, Juan Jose ; Perez-Cruz, Fernando

Channel Decoding with a Bayesian Equalizer Inproceedings

2010 IEEE International Symposium on Information Theory, pp. 1998–2002, IEEE, Austin, TX, 2010, ISBN: 978-1-4244-7892-7.

Abstract | Links | BibTeX | Tags: a posteriori probability, Bayesian equalizer, Bayesian methods, BER, Bit error rate, Channel Coding, channel decoding, channel estate information, Communication channels, Decoding, equalisers, Equalizers, error statistics, low-density parity-check decoders, LPDC decoders, Maximum likelihood decoding, maximum likelihood detection, maximum likelihood estimation, Noise reduction, parity check codes, Probability, Uncertainty

2009

Inproceedings

Djuric, Petar M; Miguez, Joaquin

Model Assessment with Kolmogorov-Smirnov Statistics Inproceedings

2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2973–2976, IEEE, Taipei, 2009, ISSN: 1520-6149.

Abstract | Links | BibTeX | Tags: Bayesian methods, Computer Simulation, Context modeling, Electronic mail, Filtering, ill-conditioned problem, Kolmogorov-Smirnov statistics, model assessment, modelling, Predictive models, Probability, statistical analysis, statistics, Testing

Martino, Luca ; Miguez, Joaquin

A Novel Rejection Sampling Scheme for Posterior Probability Distributions Inproceedings

2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2921–2924, IEEE, Taipei, 2009, ISSN: 1520-6149.

Abstract | Links | BibTeX | Tags: Additive noise, arbitrary target probability distributions, Bayes methods, Bayesian methods, Monte Carlo integration, Monte Carlo methods, Monte Carlo techniques, Overbounding, posterior probability distributions, Probability density function, Probability distribution, Proposals, Rejection sampling, rejection sampling scheme, Sampling methods, Signal processing algorithms, signal sampling, Upper bound

Achutegui, Katrin ; Martino, Luca ; Rodas, Javier ; Escudero, Carlos J; Miguez, Joaquin

A Multi-Model Particle Filtering Algorithm for Indoor Tracking of Mobile Terminals Using RSS Data Inproceedings

2009 IEEE International Conference on Control Applications, pp. 1702–1707, IEEE, Saint Petersburg, 2009, ISBN: 978-1-4244-4601-8.

Abstract | Links | BibTeX | Tags: Bayesian methods, Control systems, Filtering algorithms, generalized interacting multiple model, GIMM, indoor radio, Indoor tracking, mobile radio, mobile terminal, Monte Carlo methods, multipath propagation, position-dependent data measurement, random process, random processes, Rao-Blackwellized sequential Monte Carlo tracking, received signal strength, RSS data, Sliding mode control, State-space methods, state-space model, Target tracking, tracking, transmitter-to-receiver distance, wireless network, wireless technology

Goez, Roger ; Lazaro, Marcelino

Training of Neural Classifiers by Separating Distributions at the Hidden Layer Inproceedings

2009 IEEE International Workshop on Machine Learning for Signal Processing, pp. 1–6, IEEE, Grenoble, 2009, ISBN: 978-1-4244-4947-7.

Abstract | Links | BibTeX | Tags: Artificial neural networks, Bayesian methods, Cost function, Curve fitting, Databases, Function approximation, Neural networks, Speech recognition, Support vector machine classification, Support vector machines