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68篇 您的检索式：作者名="Emmanuel Candes"

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	题名	作者	年代	出处	被引量
1	Enhancing Sparsity by Reweighted ? 1 Minimization显示文摘	Emmanuel J. Candès Michael B. Wakin Stephen P. Boyd	2008	Journal of Fourier Analysis and Applications2008，，5：	3
2	The restricted isometry property and its implications for compressed sensing显示文摘	Emmanuel J. Candès	2008	Comptes rendus - Mathématique2008，，9：	2
3	Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions显示文摘	Emmanuel J. Candes Justin Romberg	2006	Foundations of Computational Mathematics2006，，2：	2
4	Enhancing Sparsity by Reweighted ? 1 Minimization显示文摘	Emmanuel J. Candès Michael B. Wakin Stephen P. Boyd	2008	Journal of Fourier Analysis and Applications (-)2008，，5：	1
5	Robust principal component analysis? 显示文摘	Emmanuel J Cands Li Xiaodong Ma Yi	2011	Journal of the ACM (JACM)2011，58，3：	1
6	Ro-bust uncertainty principles:exact signal reconstruction from highly incomplete frequency information 显示文摘	Emmanuel Candes Justin Romberg Terence Tao	2006	IEEE Transactions on Inform-ation Theory2006，52，2：	1
7	Robust principal component analysis?显示文摘	Emmanuel J. Candès Xiaodong Li Yi Ma John Wright	2011	Journal of the ACM (JACM)2011，，3：	1
8	Ro- bust uncertainty prineiples: Exact signal reconstruction from highly incomplete frequency information 显示文摘	Emmanuel Candes Justin Romberg Terence Tao	2006	IEEE Transactions on Information Theory2006，52，2：	1
9	Near optimal signal re- covery from random projections: Universal encoding strat- egies? 显示文摘	Emmanuel Candes Terence Tao	2006	IEEE Transactiols on Information Theory2006，52，12：	1
10	Exact Matrix Completion via Convex Optimization显示文摘	Emmanuel J. Candès Benjamin Recht	2009	Foundations of Computational Mathematics2009，，6：	1
11	Robustuncertainty principles:Exact signal reconstruct-Ion fromhighly incomplete frequency information显示文摘	Emmanuel Candes Justin Romberg Terence Tao	2006	IEEE Transac-tions on Information Theory2006，52，2：	1
12	The curvelet transform for image denoising显示文摘	Jean-Luc Starck Emmanuel J Candes David L Donoho	2002	IEEE Transactions on Image Processing2002，11，6：	1
13	NESTA:A fast and accurate first-order method for sparse recovery显示文摘	Stephen Becker Jerome Bobin Emmanuel J Candes	2011	SIAM Journal on Imaging Sciences2011，4，1：	1
14	Ro- bust uncertainty principles: exact signal reconstruction from highly incomplete frequency information 显示文摘	Emmanuel Candes Justin Romberg Terence Tao	2006	IEEE Transactions on Information Theory2006，52，2：	1
15	Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions显示文摘	Emmanuel J. Candes Justin Romberg	2006	Foundations of Computational Mathematics2006，，2：	1
16	Quantitative robust uncertainty principles and optimally sparse decompositions显示文摘	CANDES Emmanuel ROMBERG Justin		0，，02：	1
17	An intro-duction to compressive sampling显示文摘	EMMANUEL J Candès WAKIN Michael B	2008	Signal ProcessingMagazine IEEE2008，25，2：	1
18	Robust un- certainty principles:exact signal reconstruction from highly incomplete frequency information 显示文摘	Emmanuel Candes Justin Romberg Terence Tao	2006	IEEE Transactions on Information Theory2006，52，2：	1
19	Compressive sampling显示文摘	EMMANUEL J CANDE S	2006	Proceedings of the International Congress of Mathematicians2006，，3：	1
20	Robust principal component analysis?显示文摘	Emmanuel J Candes Xiaodong Li Yi Ma John Wright	2011	Journal of the ACM2011，58，3：	1

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