D. Donoho, Compressed sensing, IEEE Transactions on Information Theory, vol.52, issue.4, pp.489-509, 2006.
DOI : 10.1109/TIT.2006.871582
URL : https://hal.archives-ouvertes.fr/inria-00369486

E. Candès, J. Romberg, and T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Transactions on Information Theory, vol.52, issue.2, pp.489-509, 2006.
DOI : 10.1109/TIT.2005.862083

J. Bobin, J. Starck, and R. Ottensamer, Compressed Sensing in Astronomy, IEEE Journal of Selected Topics in Signal Processing, vol.2, issue.5, pp.718-726, 2008.
DOI : 10.1109/JSTSP.2008.2005337

M. Elad, B. Matalon, J. Shtok, and M. Zibulevsky, A wide-angle view at iterated shrinkage algorithms, Wavelets XII, 2007.
DOI : 10.1117/12.741299

I. Daubechies, M. Defrise, and C. Mol, An iterative thresholding algorithm for linear inverse problems with a sparsity constraint, Communications on Pure and Applied Mathematics, vol.58, issue.11, pp.1412-1457, 2004.
DOI : 10.1002/cpa.20042

T. Blumensath and M. Davies, Iterative Thresholding for Sparse Approximations, Journal of Fourier Analysis and Applications, special issue on sparsity, 2008.
DOI : 10.1007/s00041-008-9035-z

D. Needel and J. Tropp, CoSaMP, Accepted to Appl. Comp. Harmonic Anal, 2008.
DOI : 10.1145/1859204.1859229

W. Dai and O. Milenkovic, Subspace Pursuit for Compressive Sensing Signal Reconstruction, IEEE Transactions on Information Theory, vol.55, issue.5
DOI : 10.1109/TIT.2009.2016006
URL : http://arxiv.org/abs/0803.0811

D. L. Donoho and J. Tanner, Neighborliness of randomly projected simplices in high dimensions, Proceedings of the National Academy of Sciences, vol.102, issue.27, pp.9452-9457, 2005.
DOI : 10.1073/pnas.0502258102

D. L. Donoho, I. Drori, Y. Tsaig, and J. L. Starck, Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit, IEEE Transactions on Information Theory, vol.58, issue.2
DOI : 10.1109/TIT.2011.2173241

D. L. Donoho and Y. Tsaig, Fast Solution of '1-norm Minimization Problems When the Solution May be Sparse, IEEE Transactions on Information Theory, 2008.