A new paper from the group has been published in IEEE Signal Processing Magazine

The following paper from the group has been publishedin IEEE Signal Processing Magazine: Monica F Bugallo, Victor Elvira, Luca Martino, David Luengo, Joaquin Miguez, Petar M Djuric. “Adaptive Importance Sampling: The past, the present, and the future”, IEEE Signal Processing Magazine (Volume: 34, Issue: 4, July 2017). Abstract: A fundamental problem in signal processing is the…

A new paper from the group has been published in the MDPI Entropy

The following paper from the group has been published in the MDPI Entropy: Melanie F. Pradier, Pablo M. Olmos and Fernando Perez-Cruz, “Entropy-Constrained Scalar Quantization with a Lossy-Compressed Bit”, MDPI Entropy 2016 volume 18, issue 12. Abstract We consider the compression of a continuous real-valued source X using scalar quantizers and average squared error distortion…

A new paper from the group has been accepted for publication in Digital Signal Processing

The paper “Cooperative Parallel Particle Filters for online model selection and applications to Urban Mobility” by L. Martino, J. Read, V. Elvira, and F. Louzada has been accepted for publication in Digital Signal Processing. Abstract We design a sequential Monte Carlo scheme for the dual purpose of Bayesian inference and model selection. We consider the application context of…

New paper accepted for publication in the IEEE Trans. Signal Process

“The paper “Multiantenna GLR Detection of Rank-One Signals with a Known Power Spectral Shape under Spatially Uncorrelated Noise” by  J. Sala-Alvarez, G. Vazquez-Vilar,  R. Lopez-Valcarce, S. Sedighi and A. Taherpour has been accepted for publication in the IEEE Transactions on Signal Processing. Abstract: We establish the generalized likelihood ratio (GLR) test for a Gaussian signal of known power spectral shape and…

New paper has been published in the Proceedings of the IEEE

The following paper from the group has been published in the Proceedings of the IEEE: G. Durisi, T. Koch, and P. Popovski, “Towards massive, ultrareliable, and low-latency wireless communication with short packets,” Proceedings of the IEEE, Vol. 104, No. 9, September 2016. Abstract: Most of the recent advances in the design of high-speed wireless systems…

New paper accepted for publication in Signal Processing

The paper “Effective Sample Size for Importance Sampling Based on the Discrepancy Measures” by L. Martino, V. Elvira, and F. Louzada has been accepted for publication in Signal Processing. Abstract: The Effective Sample Size (ESS) is an important measure of efficiency of Monte Carlo methods such as Markov Chain Monte Carlo (MCMC) and Importance Sampling (IS) techniques.…

New paper accepted for pubication in IEEE Signal Processing Letters

The paper “Heretical Multiple Importance Sampling” by V. Elvira, L. Martino, D. Luengo, and M. Bugallo has been accepted for publication in IEEE Signal Processing Letters. Abstract: Multiple Importance Sampling (MIS) methods approximate moments of complicated distributions by drawing samples from a set of proposal distributions. Several ways to compute the importance weights assigned to each…

New paper accepted for publication in Digital Signal Processing

The paper “Orthogonal Parallel MCMC Methods for Sampling and Optimization” by L. Martino, V. Elvira, D. Luengo, J. Corander, and F. Louzada has been accepted for publication in Digital Signal Processing. Abstract: Monte Carlo (MC) methods are widely used in statistics, signal processing and machine learning. A well-known class of MC methods are Markov Chain Monte Carlo (MCMC)…

New paper accepted for publication in Signal Processing

The paper “Improving Population Monte Carlo: Alternative Weighting and Resampling Schemes” by  V. Elvira, L. Martino, D. Luengo, and M. Bugallo has been accepted for publication in Signal Processing Abstract: Population Monte Carlo (PMC) sampling methods are powerful tools for approximating distributions of static unknowns given a set of observations. These methods are iterative in nature: at…