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Challenging Restricted Isometry Constants with Greedy Pursuit

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Date
2009-04
Link to item file
http://hal.archives-ouvertes.fr/hal-00373450/en/
Dewey
Traitement du signal
Sujet
Compressed sensing; compressive sampling; random matrices; restricted isometry constants; sparsity
Conference name
2009 IEEE Information Theory Workshop
Conference date
10-2009
Conference city
Taormine
Conference country
Italie
URI
https://basepub.dauphine.fr/handle/123456789/3469
Collections
  • CEREMADE : Publications
Metadata
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Author
Dossal, Charles
Peyré, Gabriel
Fadili, Jalal
Type
Communication / Conférence
Abstract (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.

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