IEICE Electronics Express | |
Joint-sparse recovery in distributed networks via cooperative support fusion | |
Zha Song1  Liu Peiguo1  Huang Jijun1  Li Gaosheng1  | |
[1] College of Electronic Science and Engineering, National University of Defense Technology | |
关键词: compressed sensing; joint-sparse recovery; multiple measurement vectors; distributed networks; partially known support; | |
DOI : 10.1587/elex.10.20130738 | |
学科分类:电子、光学、磁材料 | |
来源: Denshi Jouhou Tsuushin Gakkai | |
【 摘 要 】
References(14)In this letter, we consider the problem of finding sparse signals that share the same support set from their compressed measurements collected at individual sensors in distributed networks, where each sensor has limitations in computational capability and communication power/bandwidth. In order to deal with this problem, we propose a new iterative algorithm which alternates between compressed reconstruction with partially known support at each sensor and adaptive learning support information via cooperative support fusion among sensors. Compared with other existing algorithms, the results obtained by the proposed algorithm show a significant improvement in both noiseless and noisy environments.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201911300117694ZK.pdf | 1431KB | download |