Random matrices and applications to statistical signal processing

In this thesis, we consider the problem of source localization in large sensor networks, when the number of antennas of the network and the number of samples of the observed signal are large and of the same order of magnitude. We also consider the case where the source signals are deterministic, and we develop an improved algorithm for source localization, based on the MUSIC method. For this, we fist show new results concerning the position of the eigen values of large information plus noise complex gaussian random matrices

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Source https://pastel.hal.science/tel-00660736
Author Vallet, Pascal
Maintainer CCSD
Last Updated May 26, 2026, 14:21 (UTC)
Created May 26, 2026, 14:21 (UTC)
Identifier NNT: 2011PEST1055
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire d'Informatique Gaspard-Monge (LIGM) ; Université Paris-Est Marne-la-Vallée (UPEM)-École nationale des ponts et chaussées (ENPC)-ESIEE Paris-Fédération de Recherche Bézout (BEZOUT) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
creator Vallet, Pascal
date 2011-11-28T00:00:00
harvest_object_id 3b3b9a61-08eb-4cb6-8ab9-62fce296ffa7
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-05-08T00:00:00
set_spec type:THESE