Challenging Restricted Isometry Constants with Greedy Pursuit

dc.contributor.author	Dossal, Charles
dc.contributor.author	Peyré, Gabriel HAL ID: 1211
dc.contributor.author	Fadili, Jalal HAL ID: 15510
dc.date.accessioned	2010-02-16T09:33:11Z
dc.date.available	2010-02-16T09:33:11Z
dc.date.issued	2009-04
dc.identifier.uri	https://basepub.dauphine.fr/handle/123456789/3469
dc.language.iso	en	en
dc.subject	Compressed sensing	en
dc.subject	compressive sampling	en
dc.subject	random matrices	en
dc.subject	restricted isometry constants	en
dc.subject	sparsity	en
dc.subject.ddc	621.3	en
dc.title	Challenging Restricted Isometry Constants with Greedy Pursuit	en
dc.type	Communication / Conférence
dc.description.abstracten	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.	en
dc.identifier.urlsite	http://hal.archives-ouvertes.fr/hal-00373450/en/	en
dc.description.sponsorshipprivate	oui	en
dc.subject.ddclabel	Traitement du signal	en
dc.relation.conftitle	2009 IEEE Information Theory Workshop	en
dc.relation.confdate	2009-10
dc.relation.confcity	Taormine	en
dc.relation.confcountry	Italie	en

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