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
TypeCommunication / Conférence
External document linkhttp://hal.archives-ouvertes.fr/hal-00373450/en/
Conference title2009 IEEE Information Theory Workshop
MetadataShow full item record
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 / KeywordsCompressed sensing; compressive sampling; random matrices; restricted isometry constants; sparsity
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Fadili, Jalal; Dossal, Charles; Peyré, Gabriel; Deledalle, Charles-Alban; Vaiter, Samuel (2013) Article accepté pour publication ou publié