Compressed sensing with unknown sensor permutation - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Compressed sensing with unknown sensor permutation

Résumé

Compressed sensing is the ability to retrieve a sparse vector from a set of linear measurements. The task gets more difficult when the sensing process is not perfectly known. We address such a problem in the case where the sensors have been permuted, i.e., the order of the measurements is unknown. We propose a branch-and-bound algorithm that converges to the solution. The experimental study shows that our approach always retrieves the unknown permutation, while a simple convex relaxation strategy almost always fails. In terms of its time complexity, we show that the proposed algorithm converges quickly with respect to the combinatorial nature of the problem.
Fichier principal
Vignette du fichier
PermutationIcassp.pdf (198.97 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00881407 , version 1 (08-11-2013)
hal-00881407 , version 2 (22-04-2014)

Identifiants

Citer

Valentin Emiya, Antoine Bonnefoy, Laurent Daudet, Rémi Gribonval. Compressed sensing with unknown sensor permutation. ICASSP - IEEE International Conference on Acoustics Speech and Signal Processing, May 2014, Florence, Italy. ⟨10.1109/ICASSP.2014.6853755⟩. ⟨hal-00881407v2⟩
984 Consultations
1217 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More