期刊
IET SIGNAL PROCESSING
卷 13, 期 5, 页码 495-505出版社
WILEY
DOI: 10.1049/iet-spr.2018.5037
关键词
matrix algebra; numerical analysis; signal reconstruction; compressed sensing; minimisation; signal denoising; sharp sufficient condition; block signal recovery; block restricted isometry property; block structure; block sparse signal; noise-free case; $l_2; l_1$l2; l1 minimisation
资金
- Natural Science Foundation of China [61673015, 61273020]
- Fundamental Research Funds for the Central Universities [XDJK2015A007, XDJK2018C076, SWU1809002]
- Youth Science and technology talent development project [Qian jiao he KY zi [2018]313]
- Science and technology Foundation of Guizhou province [Qian ke he Ji Chu [2016]1161]
- Guizhou province natural science foundation in China [Qian Jiao He KY [2016]255]
This work gains a sharp sufficient condition on the block restricted isometry property for the recovery of sparse signal and corresponding upper bound estimate of error. Under the certain assumption, the signal with block structure can be stably recovered in the presence of noisy case and the block sparse signal can be exactly reconstructed in the noise-free case. Besides, an example is proposed to exhibit the condition is sharp. Numerical simulations are carried out to demonstrate that authors' results are verifiable and l(2)/l(1) minimisation method is robust and stable for the recovery of block sparse signals.
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