Exact Reconstruction of Sparse Signals via Nonconvex Minimization

作者: Rick Chartrand

DOI: 10.1109/LSP.2007.898300

关键词:

摘要: Several authors have shown recently that It is possible to reconstruct exactly a sparse signal from fewer linear measurements than would be expected from traditional sampling theory. …

参考文章(10)
Scott Shaobing Chen, David L. Donoho, Michael A. Saunders, Atomic Decomposition by Basis Pursuit SIAM Journal on Scientific Computing. ,vol. 20, pp. 33- 61 ,(1998) , 10.1137/S1064827596304010
B. K. Natarajan, Sparse Approximate Solutions to Linear Systems SIAM Journal on Computing. ,vol. 24, pp. 227- 234 ,(1995) , 10.1137/S0097539792240406
Rick Chartrand, Nonconvex Compressed Sensing and Error Correction international conference on acoustics, speech, and signal processing. ,vol. 3, pp. 889- 892 ,(2007) , 10.1109/ICASSP.2007.366823
Emmanuel Candes, Mark Rudelson, Terence Tao, Roman Vershynin, Error correction via linear programming foundations of computer science. pp. 668- 681 ,(2005) , 10.1109/SFCS.2005.5464411
E.J. Candes, T. Tao, Decoding by linear programming IEEE Transactions on Information Theory. ,vol. 51, pp. 4203- 4215 ,(2005) , 10.1109/TIT.2005.858979
Emmanuel J. Candes, Terence Tao, Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? IEEE Transactions on Information Theory. ,vol. 52, pp. 5406- 5425 ,(2006) , 10.1109/TIT.2006.885507
B.D. Rao, K. Kreutz-Delgado, An affine scaling methodology for best basis selection IEEE Transactions on Signal Processing. ,vol. 47, pp. 187- 200 ,(1999) , 10.1109/78.738251
E.J. Candes, J. Romberg, T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information IEEE Transactions on Information Theory. ,vol. 52, pp. 489- 509 ,(2006) , 10.1109/TIT.2005.862083
Emmanuel J Candes, Justin K Romberg, Terence Tao, None, Stable signal recovery from incomplete and inaccurate measurements Communications on Pure and Applied Mathematics. ,vol. 59, pp. 1207- 1223 ,(2006) , 10.1002/CPA.20124
D.L. Donoho, Compressed sensing ,(2004)