A new paper from the group has been accepted for publication in the IEEE Transactions on Signal Processing

The paper “Monte Carlo Methods through an Online Scheme for Convergence Assessment” by Víctor Elvira, Joaquín Míguez and Petar M. Djuric has been accepted for publication inthe IEEE Transactions on Signal Processing. Abstract Particle filters are broadly used to approximate posterior distributions of hidden states in state-space models by means of sets of weighted particles. While…

DroidsareHacking Team wins Hackathon Telefónica Third Prize

October, 2016 DroidsareHacking Team wins Hackathon Telefónica Third Prize. The DroidsareHacking Team is composed of Juanjo Campaña (GTS Group), Miguel Molina and Juan de Toro. The prizes are supported by Telefónica and Qualcomm Technologies. The goal of this initiative is the development of mobile applications based on Qualcomm Snapdragon processor that contribute to the improvement…

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…

Tobias Koch awarded ERC Starting Grant

Tobias Koch awarded ERC Starting Grant Tobias Koch, who is a Visiting Professor and Ramón y Cajal Research Fellow in our group, has been awarded the prestigious ERC Starting Grant, which is given every year to the best young researchers in Europe. He will receive funding from the ERC for the next 5 years to…

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…

Invited talk: Bernhard Geiger (TU Munich, Germany)

Join us for an invited talk with Bernhard Geiger (TU Munich, Germany) Title: “Information-Theory for Markov Aggregation and Clustering” Event Date: September 6, 12:00-13:00. Location: Room 4.2.E03; Torres Quevedo Building; Leganés Campus; Universidad Carlos III de Madrid. Abstract: In many scientific disciplines, Markov models are too large to allow efficient simulation or parameter estimation –…

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)…