ENHANCED BLOCK-SPARSE SIGNAL RECOVERY PERFORMANCE VIA TRUNCATED e2/e1-2 MINIMIZATION |
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| Authors: | Weichao Kong Jianjun Wang Wendong Wang & Feng Zhang |
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| Institution: | School of Mathematics and Statistics, Southwest University, Chongqing 400715, China;School of Mathematics and Statistics, Southwest University, Chongqing 400715, China;Research Center for Artificial Intelligence Education Big Data, Southwest University,Chongqing 400715, China |
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| Abstract: | In this paper, we investigate truncated $?_2/?_{1?2}$ minimization and its associated alternating direction method of multipliers (ADMM) algorithm for recovering the block sparse
signals. Based on the block restricted isometry property (Block-RIP), a theoretical analysis is presented to guarantee the validity of proposed method. Our theoretical results
not only show a less error upper bound, but also promote the former recovery condition
of truncated ?1?2 method for sparse signal recovery. Besides, the algorithm has been
compared with some state-of-the-art algorithms and numerical experiments have shown
excellent performances on recovering the block sparse signals. |
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| Keywords: | Compressed sensing Block-sparse Truncated $?_2/?_{1?2}$ minimization method ADMM |
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