Conference Publications

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Martino, Luca; Elvira, Victor; Luengo, David; Artés-Rodríguez, Antonio; Corander, Jukka

Smelly Parallel MCMC Chains Inproceedings

In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4070–4074, IEEE, Brisbane, 2015, ISBN: 978-1-4673-6997-8.

Abstract | Links | BibTeX | Tags: Bayesian inference, learning (artificial intelligence), Machine learning, Markov chain Monte Carlo, Markov chain Monte Carlo algorithms, Markov processes, MC methods, MCMC algorithms, MCMC scheme, mean square error, mean square error methods, Monte Carlo methods, optimisation, parallel and interacting chains, Probability density function, Proposals, robustness, Sampling methods, Signal processing, Signal processing algorithms, signal sampling, smelly parallel chains, smelly parallel MCMC chains, Stochastic optimization


Valera, Isabel; Ruiz, Francisco J R; Perez-Cruz, Fernando

Infinite Factorial Unbounded Hidden Markov Model for Blind Multiuser Channel Estimation Inproceedings

In: 2014 4th International Workshop on Cognitive Information Processing (CIP), pp. 1–6, IEEE, Copenhagen, 2014, ISBN: 978-1-4799-3696-0.

Abstract | Links | BibTeX | Tags: Bayes methods, Bayesian non parametrics, Bayesian nonparametric models, blind multiuser channel estimation, Channel estimation, degrees of freedom, detection problems, dispersive channel model, generative model, Hidden Markov models, HMM, inference algorithm, infinite factorial unbounded hidden Markov model, Markov chain Monte Carlo, Markov processes, MIMO, MIMO communication, MIMO communication systems, multiple-input multiple-output (MIMO), multiple-input multiple-output communication syste, receiver performance, Receivers, Signal to noise ratio, Transmitters, unbounded channel length, unbounded number, user detection


Balasingam, Balakumar; Bolic, Miodrag; Djuric, Petar M; Miguez, Joaquin

Efficient Distributed Resampling for Particle Filters Inproceedings

In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3772–3775, IEEE, Prague, 2011, ISSN: 1520-6149.

Abstract | Links | BibTeX | Tags: Approximation algorithms, Copper, Covariance matrix, distributed resampling, Markov processes, Probability density function, Sequential Monte-Carlo methods, Signal processing, Signal processing algorithms

Achutegui, Katrin; Miguez, Joaquin

A Parallel Resampling Scheme and its Application to Distributed Particle Filtering in Wireless Networks Inproceedings

In: 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 81–84, IEEE, San Juan, 2011, ISBN: 978-1-4577-2105-2.

Abstract | Links | BibTeX | Tags: Approximation algorithms, Approximation methods, Artificial neural networks, distributed resampling, DRNA technique, Markov processes, nonproportional allocation algorithm, parallel resampling scheme, PF, quantization, Signal processing, Vectors, Wireless sensor network, Wireless Sensor Networks, WSN


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

Bayesian BCJR for Channel Equalization and Decoding Inproceedings

In: 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