Year: 2020
Author: Weichao Kong, Jianjun Wang, Wendong Wang, Feng Zhang
Journal of Computational Mathematics, Vol. 38 (2020), Iss. 3 : pp. 437–451
Abstract
In this paper, we investigate truncated $ℓ_2/ℓ_{1−2}$ 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 ℓ1−2 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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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/jcm.1811-m2017-0275
Journal of Computational Mathematics, Vol. 38 (2020), Iss. 3 : pp. 437–451
Published online: 2020-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 15
Keywords: Compressed sensing Block-sparse Truncated $ℓ_2/ℓ_{1−2}$ minimization method ADMM.
Author Details
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