D. L. Donoho, For most large underdetermined systems of linear equations the minimal ???1-norm solution is also the sparsest solution, Communications on Pure and Applied Mathematics, vol.50, issue.6, 2004.
DOI : 10.1002/cpa.20132

M. Zibulevsky and B. A. Pearlmutter, Blind Source Separation by Sparse Decomposition in a Signal Dictionary, Neural Computation, vol.1, issue.4, pp.863-882, 2001.
DOI : 10.1016/S0042-6989(97)00169-7

R. Gribonval and S. Lesage, A survey of sparse component analysis for blind source separation: principles, perspectives, and new challanges, Proceeding of ESANN'06, pp.323-330, 2006.

D. L. Donoho, M. Elad, and V. Temlyakov, Stable recovery of sparse overcomplete representations in the presence of noise, IEEE Transactions on Information Theory, vol.52, issue.1, pp.6-18, 2006.
DOI : 10.1109/TIT.2005.860430

M. Davies and N. Mitianoudis, Simple mixture model for sparse overcomplete ICA, IEE Proceeding on Visual Image and Signal Processing, pp.35-43, 2004.
DOI : 10.1049/ip-vis:20040304

Y. Q. Li, S. Amari, A. Cichocki, D. W. Ho, and S. Xie, Underdetermined blind source separation based on sparse representation, IEEE Transaction on Signal Processing, vol.54, issue.2, pp.423-437, 2006.

G. H. Mohimani, M. Babaie-zadeh, and C. Jutten, Fast Sparse Representation Based on Smoothed ???0 Norm, 2007.
DOI : 10.1007/978-3-540-74494-8_49

URL : https://hal.archives-ouvertes.fr/hal-00173357

H. Zayyani, M. Babaie-zadeh, and C. Jutten, Source Estimation in Noisy Sparse Component Analysis, 2007 15th International Conference on Digital Signal Processing, 2007.
DOI : 10.1109/ICDSP.2007.4288558

URL : https://hal.archives-ouvertes.fr/hal-00173337

S. S. Chen, D. L. Donoho, and M. A. Saunders, Atomic decomposition by basis pursuit, In: SIAM Journal on Scientific Computing, vol.20, issue.1, pp.31-61, 1999.