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A low complexity Orthogonal Matching Pursuit for sparse signal approximation with shift-invariant dictionaries

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4 Author(s)
Mailhe, B. ; Centre de Rech. INRIA Rennes -Bretagne Atlantique, IRISA, Rennes ; Gribonval, R. ; Bimbot, F. ; Vandergheynst, P.

We propose a variant of orthogonal matching pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift-invariant signal dictionaries with localized atoms, such as time-frequency dictionaries, and achieves approximation performance comparable to OMP at a computational cost similar to matching pursuit. Numerical experiments with a large audio signal show that, compared to OMP and gradient pursuit, the proposed algorithm runs in over 500 less time while leaving the approximation error almost unchanged.

Published in:

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Date of Conference:

19-24 April 2009