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Martino, Luca; Elvira, Victor; Luengo, David; Corander, Jukka

Parallel interacting Markov adaptive importance sampling (Inproceeding)

2015 23rd European Signal Processing Conference (EUSIPCO), pp. 499–503, IEEE, Nice, 2015, ISBN: 978-0-9928-6263-3.

(Abstract | Links | BibTeX | Tags: Adaptive importance sampling, Bayesian inference, MCMC methods, Monte Carlo methods, Parallel Chains, Probability density function, Proposals, Signal processing, Signal processing algorithms, Sociology)

Elvira, Victor; Martino, Luca; Luengo, David; Corander, Jukka

A Gradient Adaptive Population Importance Sampler (Inproceeding)

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4075–4079, IEEE, Brisbane, 2015, ISBN: 978-1-4673-6997-8.

(Abstract | Links | BibTeX | Tags: adaptive extensions, adaptive importance sampler, Adaptive importance sampling, gradient adaptive population, gradient matrix, Hamiltonian Monte Carlo, Hessian matrices, Hessian matrix, learning (artificial intelligence), Machine learning, MC methods, Monte Carlo, Monte Carlo methods, population Monte Carlo (PMC), proposal densities, Signal processing, Sociology, statistics, target distribution)

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

Smelly Parallel MCMC Chains (Inproceeding)

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)



Miguez, Joaquin

On the uniform asymptotic convergence of a distributed particle filter (Inproceeding)

2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), pp. 241–244, IEEE, A Coruña, 2014, ISBN: 978-1-4799-1481-4.

(Abstract | Links | BibTeX | Tags: ad hoc networks, Approximation algorithms, approximation errors, Approximation methods, classical convergence theorems, Convergence, convergence of numerical methods, distributed particle filter scheme, distributed signal processing algorithms, Monte Carlo methods, parallel computing systems, particle filtering (numerical methods), Signal processing, Signal processing algorithms, stability assumptions, uniform asymptotic convergence, Wireless Sensor Networks, WSNs)


Journal Articles

Perez-Cruz, Fernando; Van Vaerenbergh, Steven; Murillo-Fuentes, Juan Jose; Lazaro-Gredilla, Miguel; Santamaria, Ignacio

Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances (Journal Article)

IEEE Signal Processing Magazine, 30 (4), pp. 40–50, 2013, ISSN: 1053-5888.

(Abstract | Links | BibTeX | Tags: adaptive algorithm, Adaptive algorithms, classification scenario, Gaussian processes, Learning systems, Machine learning, Noise measurement, nonGaussian noise model, Nonlinear estimation, nonlinear estimation problem, nonlinear signal processing, optimal Wiener filtering, recursive algorithm, Signal processing, Wiener filters, wireless digital communication)


Luengo, David; Via, Javier; Monzon, Sandra; Trigano, Tom; Artés-Rodríguez, Antonio

Cross-Products LASSO (Inproceeding)

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 6118–6122, IEEE, Vancouver, 2013, ISSN: 1520-6149.

(Abstract | Links | BibTeX | Tags: Approximation methods, approximation theory, concave programming, convex programming, Cost function, cross-product LASSO cost function, Dictionaries, dictionary, Encoding, LASSO, learning (artificial intelligence), negative co-occurrence, negative cooccurrence phenomenon, nonconvex optimization problem, Signal processing, signal processing application, signal reconstruction, sparse coding, sparse learning approach, Sparse matrices, sparsity-aware learning, successive convex approximation, Vectors)



Koch, Tobias; Martinez, Alfonso; i Fabregas, Albert Guillen

The Capacity Loss of Dense Constellations (Inproceeding)

2012 IEEE International Symposium on Information Theory Proceedings, pp. 572–576, IEEE, Cambridge, MA, 2012, ISSN: 2157-8095.

(Abstract | Links | BibTeX | Tags: capacity loss, channel capacity, Constellation diagram, dense constellations, Entropy, general complex-valued additive-noise channels, high signal-to-noise ratio, loss 1.53 dB, power loss, Quadrature amplitude modulation, Random variables, signal constellations, Signal processing, Signal to noise ratio, square signal constellations, Upper bound)



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

Efficient Distributed Resampling for Particle Filters (Inproceeding)

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 (Inproceeding)

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)



Djuric, Petar; Closas, Pau; Bugallo, Monica; Miguez, Joaquin

Evaluation of a Method's Robustness (Inproceeding)

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3598–3601, IEEE, Dallas, 2010, ISSN: 1520-6149.

(Abstract | Links | BibTeX | Tags: Electronic mail, Extraterrestrial measurements, Filtering, Gaussian processes, method's robustness, Random variables, robustness, sequential methods, Signal processing, statistical distributions, Telecommunications, uniform distribution, Wireless communication)



Maiz, Cristina; Miguez, Joaquin; Djuric, Petar

Particle Filtering in the Presence of Outliers (Inproceeding)

2009 IEEE/SP 15th Workshop on Statistical Signal Processing, pp. 33–36, IEEE, Cardiff, 2009, ISBN: 978-1-4244-2709-3.

(Abstract | Links | BibTeX | Tags: computer simulations, Degradation, Filtering, multidimensional random variates, Multidimensional signal processing, Multidimensional systems, Nonlinear tracking, Outlier detection, predictive distributions, Signal processing, signal processing tools, signal-power observations, spatial depth, statistical analysis, statistical distributions, statistics, Target tracking, Testing)

Vinuelas-Peris, Pablo; Artés-Rodríguez, Antonio

Sensing Matrix Optimization in Distributed Compressed Sensing (Inproceeding)

2009 IEEE/SP 15th Workshop on Statistical Signal Processing, pp. 638–641, IEEE, Cardiff, 2009, ISBN: 978-1-4244-2709-3.

(Abstract | Links | BibTeX | Tags: Compressed sensing, Computer Simulation, computer simulations, correlated signal, Correlated signals, correlation theory, Dictionaries, distributed coding strategy, distributed compressed sensing, Distributed control, efficient projection method, Encoding, joint recovery method, Matching pursuit algorithms, Optimization methods, orthogonal matching pursuit, Projection Matrix Optimization, sensing matrix optimization, Sensor Network, Sensor phenomena and characterization, Sensor systems, Signal processing, Sparse matrices, Technological innovation)



Santiago-Mozos, Ricardo; Fernandez-Lorenzana,; Perez-Cruz, Fernando; Artés-Rodríguez, Antonio

On the Uncertainty in Sequential Hypothesis Testing (Inproceeding)

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 1223–1226, IEEE, Paris, 2008, ISBN: 978-1-4244-2002-5.

(Abstract | Links | BibTeX | Tags: 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)

Vila-Forcen,; Artés-Rodríguez, Antonio; Garcia-Frias,

Compressive Sensing Detection of Stochastic Signals (Inproceeding)

2008 42nd Annual Conference on Information Sciences and Systems, pp. 956–960, IEEE, Princeton, 2008, ISBN: 978-1-4244-2246-3.

(Abstract | Links | BibTeX | Tags: 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)