Challenging Restricted Isometry Constants with Greedy Pursuit

Dossal, Charles; Peyré, Gabriel; Fadili, Jalal

Dossal, Charles; Peyré, Gabriel; Fadili, Jalal (2009-04), Challenging Restricted Isometry Constants with Greedy Pursuit, 2009 IEEE Information Theory Workshop, 2009-10, Taormine, Italie

Type

Communication / Conférence

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http://hal.archives-ouvertes.fr/hal-00373450/en/

Date

2009-04

Titre du colloque

2009 IEEE Information Theory Workshop

Date du colloque

2009-10

Ville du colloque

Taormine

Pays du colloque

Italie

Métadonnées

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Auteur(s)

Dossal, Charles
Peyré, Gabriel
Fadili, Jalal

Résumé (EN)

This paper proposes greedy numerical schemes to compute lower bounds of the restricted isometry constants that are central in compressed sensing theory. Matrices with small restricted isometry constants enable stable recovery from a small set of random linear measurements. We challenge this compressed sampling recovery using greedy pursuit algorithms that detect ill-conditionned sub-matrices. It turns out that these sub-matrices have large isometry constants and hinder the performance of compressed sensing recovery.

Mots-clés

Compressed sensing; compressive sampling; random matrices; restricted isometry constants; sparsity