Fast orthogonal sparse approximation algorithms over local dictionaries

Boris Mailhé 1 Rémi Gribonval 1 Pierre Vandergheynst 2 Frédéric Bimbot 1
1 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this work we present a new greedy algorithm for sparse approximation called LocOMP. LocOMP is meant to be run on local dictionaries made of atoms with much shorter supports than the signal length. This notably encompasses shift-invariant dictionaries and time-frequency dictionaries, be they monoscale or multiscale. In this case, very fast implementations of Matching Pursuit are already available. LocOMP is almost as fast as Matching Pursuit while approaching the signal almost as well as the much slower Orthogonal Matching Pursuit.
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Dernière modification le : jeudi 11 janvier 2018 - 06:20:09
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Boris Mailhé, Rémi Gribonval, Pierre Vandergheynst, Frédéric Bimbot. Fast orthogonal sparse approximation algorithms over local dictionaries. Signal Processing, Elsevier, 2011, 〈http://www.sciencedirect.com/science/article/B6V18-51WV00K-3/2/ea5d3613cf553f760064299db3c0f5cd〉. 〈10.1016/j.sigpro.2011.01.004〉. 〈hal-00460558v3〉

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