Fast sparse representation based on smoothed lo norm

Authors:
G. Hosein Mohimani;Massoud Babaie-Zadeh;Christian Jutten
Affiliations:
Electrical Engineering Department, Advanced Communications Research Institute, Sharif University of Technology, Tehran, Iran;Electrical Engineering Department, Advanced Communications Research Institute, Sharif University of Technology, Tehran, Iran;GIPSA-lab, Department of Images and Signals, National Polytechnic Institute of Grenoble, France
Venue:
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Year:
2007

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Abstract

In this paper, a new algorithm for Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented. The algorithm is essentially a method for obtaining sufficiently sparse solutions of underdetermined systems of linear equations. The solution obtained by the proposed algorithm is compared with the minimum l1-norm solution achieved by Linear Programming (LP). It is experimentally shown that the proposed algorithm is about two orders of magnitude faster than the state-of-the-art l1-magic, while providing the same (or better) accuracy.