(conférencier invité par Farida Cheriet dans le cadre des séminaires du GRSTB)
Titre : Sparse Reconstruction Using Compressive Sensing and its Applications in Signal Processing
Conférencier : Professor Tarek Al-Naffouri, King Abdullah University of Science and Technology (KAUST), KSA
Date : jeudi 13 juin 2013 à 15h00
Lieu : salle L-4812, Pavillon Lassonde de l'École Polytechnique
Abstract:
There has been increased interest in sparse signal reconstruction algorithms (commonly known as compressed sensing) due to their wide applicability in various fields. Recently, focus has shifted to Bayesian based approaches that are able to perform sparse recovery at much lower complexity while invoking constraint and/or a priori information about the data.
In this talk, we present a novel low complexity Bayesian approach to the estimation of sparse signals. The approach jointly utilizes 1) the sparsity information of the desired signal 2) the a priori statistical information about the signal and noise and 3) the inherent structure in the sensing matrix to obtain near optimal Bayesian estimates. The proposed approach is able to deal with both Gaussian and non-Gaussian priors. The approach also exhibits relatively low complexity compared to the widely used convex relaxation methods as well as greedy matching pursuit techniques. The discussion will be illuminated with several signal processing applications including channel estimation in UWB and estimation and cancellation of noise/distortion.
Biography:
Tareq Y. Al-Naffouri received the B.S. degrees in mathematics and electrical engineering (with first honors) from King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, in 1995, the M.S. degree in electrical engineering from Georgia Institute of Technology, Atlanta, in 1998, and the Ph.D. degree in electrical engineering from Stanford University, CA, in 2004. He is currently Associate Professor at the Electrical Engineering Department at King Abdullah University of Science & Technology (KAUST) and jointly at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. His research interests lie in the areas of adaptive and statistical signal processing and in compressed sensing and their applications to wireless communications, and in multiuser information theory.
