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Block Sparse Recovery via Mixed l_2/l_1 Minimization 被引量:10

Block Sparse Recovery via Mixed l_2/l_1 Minimization
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摘要 We consider efficient methods for the recovery of block sparse signals from underdetermined system of linear equations. We show that if the measurement matrix satisfies the block RIP with δ2s 〈 0.4931, then every block s-sparse signal can be recovered through the proposed mixed l2/ll-minimization approach in the noiseless case and is stably recovered in the presence of noise and mismodeling error. This improves the result of Eldar and Mishali (in IEEE Trans. Inform. Theory 55: 5302-5316, 2009). We also give another sufficient condition on block RIP for such recovery method: 58 〈 0.307. We consider efficient methods for the recovery of block sparse signals from underdetermined system of linear equations. We show that if the measurement matrix satisfies the block RIP with δ2s 〈 0.4931, then every block s-sparse signal can be recovered through the proposed mixed l2/ll-minimization approach in the noiseless case and is stably recovered in the presence of noise and mismodeling error. This improves the result of Eldar and Mishali (in IEEE Trans. Inform. Theory 55: 5302-5316, 2009). We also give another sufficient condition on block RIP for such recovery method: 58 〈 0.307.
出处 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2013年第7期1401-1412,共12页 数学学报(英文版)
基金 Supported by National Natural Science Foundation of China (Grant Nos. 11171299 and 91130009) Natural Science Foundation of Zhejiang Province of China (Grant No. Y6090091)
关键词 Compressed sensing block RIP block sparsity mixed l2/l1 minimization Compressed sensing, block RIP, block sparsity, mixed l2/l1 minimization
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