Fast Sparse Representation Based on Smoothed L0 Norm

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 1-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 1-magic, while providing the same (or better) accuracy.
Complete list of metadatas

Cited literature [16 references]  Display  Hide  Download
Contributor : Christian Jutten <>
Submitted on : Wednesday, September 19, 2007 - 4:12:56 PM
Last modification on : Tuesday, July 9, 2019 - 1:21:28 AM
Long-term archiving on : Monday, June 27, 2011 - 4:54:15 PM


Files produced by the author(s)


  • HAL Id : hal-00173357, version 1


G. Hosein Mohimani, Massoud Babaie-Zadeh, Christian Jutten. Fast Sparse Representation Based on Smoothed L0 Norm. 7th International Conference, ICA 2007, Sep 2007, London, United Kingdom. pp.389-396. ⟨hal-00173357⟩



Record views


Files downloads