Journal
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 57, Issue 1, Pages 289-301Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2008.2007606
Keywords
Atomic decomposition; blind source separation (BSS); compressed sensing; overcomplete signal representation; sparse component analysis (SCA); sparse decomposition; sparse source separation
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Funding
- Iran National Science Foundation (INSF) [86/994]
- Center for International Research and Collabration (ISMO)
- French embassy in Tehran in the framework of a GundiShapour program
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In this paper, a fast algorithm for overcomplete sparse decomposition, called SL0, is proposed. The algorithm is essentially a method for obtaining sparse solutions of underdetermined systems of linear equations, and its applications include underdetermined sparse component analysis (SCA), atomic decomposition on overcomplete dictionaries, compressed sensing, and decoding real field codes. Contrary to previous methods, which usually solve this problem by minimizing the l(1) norm using linear programming (LP) techniques, our algorithm tries to directly minimize the l(0) norm. It is experimentally shown that the proposed algorithm is about two to three orders of magnitude faster than the state-of-the-art interior-point LP solvers, while providing the same (or better) accuracy.
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