A necessary and sufficient condition for sparse vector recovery via ℓ1 − ℓ2 minimization

Author:

Bi NingORCID,Tang Wai-Shing

Funder

Ministry of Education - Singapore

National Natural Science Foundation of China

Sun Yat-sen University

Guangdong Province Key Laboratory of Computational Science

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference24 articles.

1. A new sufficient condition for sparse vector recovery via ℓ1−ℓ2 local minimization;Bi;Anal. Appl.,2021

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3. Sparse representation of a polytope and recovery of sparse signals and low-rank matrices;Cai;IEEE Trans. Inf. Theory,2014

4. The restricted isometry property and its implications for compressed sensing;Candès;C. R. Acad. Sci., Sér. 1,2008

5. Decoding by linear programming;Candès;IEEE Trans. Inf. Theory,2005

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