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Challenging Restricted Isometry Constants with Greedy Pursuit

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
External document link
http://hal.archives-ouvertes.fr/hal-00373450/en/
Date
2009-04
Conference title
2009 IEEE Information Theory Workshop
Conference date
2009-10
Conference city
Taormine
Conference country
Italie
Metadata
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Author(s)
Dossal, Charles
Peyré, Gabriel
Fadili, Jalal
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.
Subjects / Keywords
Compressed sensing; compressive sampling; random matrices; restricted isometry constants; sparsity

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