– V. Emiya (LIF) : Compressed sensing with unknown sensor permutation
Carte non disponible

Date/heure
Date(s) - 24/01/2014
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories


Compressed sensing with unknown sensor permutation By Valentin Emiya, LIF. 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.
– V. Emiya (LIF) : Compressed sensing with unknown sensor permutation
Carte non disponible

Date/heure
Date(s) - 24/01/2014
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories


Compressed sensing with unknown sensor permutation\nBy Valentin Emiya, LIF.\n\nCompressed 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.[
– V. Emiya (LIF) : Compressed sensing with unknown sensor permutation
Carte non disponible

Date/heure
Date(s) - 24/01/2014
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories


Compressed sensing with unknown sensor permutation\nBy Valentin Emiya, LIF.\n\nCompressed 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.[