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The reweighed greedy analysis pursuit algorithm for the cosparse analysis model

  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

4 引用 (Scopus)

摘要

Recently, a cosparse analysis model has been introduced as an interesting alternative to the sparse representation synthesis model. This model is focused on zero elements in the analysis representation vector rather than non-zero elements. Hence, finding cosparse solutions is a problem of important significance in signal processing. In this paper, we construct an adaptive weighted matrix in the greedy analysis pursuit algorithm and propose the reweighed greedy analysis pursuit (ReGAP) algorithm for cosparse signal reconstruction with noise. Using a weighted matrix, we fill the gap between greedy and convex relaxation techniques. Theoretical analysis shows that our algorithm is convergent. We estimate the error bound of ReGAP algorithm with cosparse analysis model, and then simulation results demonstrate that our algorithm is feasible and effective.

源语言英语
主期刊名2015 11th International Conference on Natural Computation, ICNC 2015
编辑Zheng Xiao, Zhao Tong, Kenli Li, Xingwei Wang, Keqin Li
出版商IEEE Computer Society
页1018-1022
页数5
ISBN(电子版)9781467376792
DOI
出版状态已出版 - 8 1月 2016
活动11th International Conference on Natural Computation, ICNC 2015 - Zhangjiajie, 中国
期限: 15 8月 2015 → 17 8月 2015

丛书

姓名Proceedings - International Conference on Natural Computation
卷2016-January
ISSN(印刷版)2157-9555

会议

会议11th International Conference on Natural Computation, ICNC 2015
国家/地区中国
市Zhangjiajie
时期15/08/15 → 17/08/15

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