A LOW COMPLEXITY ORTHOGONAL MATCHING PURSUIT FOR SPARSE SIGNAL APPROXIMATION WITH SHIFT-INVARIANT DICTIONARIES

被引:34
|
作者
Mailhe, Boris [1 ]
Gribonval, Remi [1 ]
Bimbot, Frederic [1 ]
Vandergheynst, Pierre [2 ]
机构
[1] IRISA, Ctr Rech INRIA Rennes Bretagne Atlantique, Campus Beaulieu, F-35042 Rennes, France
[2] Ecole Polytech Fed Lausanne, Sch Engn, Signal Proc Labs LTS, CH-1015 Lausanne, Switzerland
关键词
sparse approximation; greedy algorithms; shift-invariance; orthogonal matching pursuit;
D O I
10.1109/ICASSP.2009.4960366
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
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.
引用
收藏
页码:3445 / +
页数:2
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