Approximate Sparse Decomposition Based on Smoothed L0-Norm
| dc.creator | Firouzi, Hamed | |
| dc.creator | Farivar, Masoud | |
| dc.creator | Babaie-Zadeh, Massoud | |
| dc.creator | Jutten, Christian | |
| dc.date | 2008-11-18 | |
| dc.date.accessioned | 2026-07-07T10:19:09Z | |
| dc.date.available | 2026-07-07T10:19:09Z | |
| dc.description | In this paper, we propose a method to address the problem of source estimation for Sparse Component Analysis (SCA) in the presence of additive noise. Our method is a generalization of a recently proposed method (SL0), which has the advantage of directly minimizing the L0-norm instead of L1-norm, while being very fast. SL0 is based on minimization of the smoothed L0-norm subject to As=x. In order to better estimate the source vector for noisy mixtures, we suggest then to remove the constraint As=x, by relaxing exact equality to an approximation (we call our method Smoothed L0-norm Denoising or SL0DN). The final result can then be obtained by minimization of a proper linear combination of the smoothed L0-norm and a cost function for the approximation. Experimental results emphasize on the significant enhancement of the modified method in noisy cases. | |
| dc.description | 4 Pages, Submitted to ICASSP 2009 | |
| dc.identifier | https://arxiv.org/abs/0811.2868 | |
| dc.identifier | http://arxiv.org/abs/0811.2868 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/174405 | |
| dc.subject | Multimedia | |
| dc.subject | Information Theory | |
| dc.title | Approximate Sparse Decomposition Based on Smoothed L0-Norm | |
| dc.type | text |