A Numerical Exploration of Compressed Sampling Recovery
Fadili, Jalal; Peyré, Gabriel; Dossal, Charles (2009-04), A Numerical Exploration of Compressed Sampling Recovery, SPARS'09, Signal Processing with Adaptive Sparse Structured Representations, 2009-04, Saint-Malo, France
Type
Communication / ConférenceExternal document link
http://hal.archives-ouvertes.fr/hal-00365028/en/Date
2009-04Conference title
SPARS'09, Signal Processing with Adaptive Sparse Structured RepresentationsConference date
2009-04Conference city
Saint-MaloConference country
FranceMetadata
Show full item recordAbstract (EN)
This paper explores numerically the efficiency of $\lun$ minimization for the recovery of sparse signals from compressed sampling measurements in the noiseless case. Inspired by topological criteria for $\lun$-identifiability, a greedy algorithm computes sparse vectors that are difficult to recover by $\ell_1$-minimization. We evaluate numerically the theoretical analysis without resorting to Monte-Carlo sampling, which tends to avoid worst case scenarios. This allows one to challenge sparse recovery conditions based on polytope projection and on the restricted isometry property.Subjects / Keywords
L1 minimization; sparsity; Compressed sensingRelated items
Showing items related by title and author.
-
Fadili, Jalal; Peyré, Gabriel; Dossal, Charles (2010) Article accepté pour publication ou publié
-
Deledalle, Charles-Alban; Vaiter, Samuel; Peyré, Gabriel; Fadili, Jalal; Dossal, Charles (2012) Communication / Conférence
-
Dossal, Charles; Fadili, Jalal; Peyré, Gabriel; Chabanol, Marie-Line (2012) Article accepté pour publication ou publié
-
Fadili, Jalal; Dossal, Charles; Peyré, Gabriel (2009) Communication / Conférence
-
Vaiter, Samuel; Deledalle, Charles-Alban; Peyré, Gabriel; Fadili, Jalal; Dossal, Charles (2012) Communication / Conférence