[1] Zhang Ruoyu, Zhao Honglin,. An improved sparsity estimation variable step-sizematching pursuit algorithm [J]. Journal of Southeast University (English Edition), 2016, 32 (2): 164-169. [doi:10.3969/j.issn.1003-7985.2016.02.006]

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An improved sparsity estimation variable step-sizematching pursuit algorithm()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

32

Issue:

2016 2

Page:

164-169

Research Field:

Information and Communication Engineering

Publishing date:

2016-06-20

Info

Title:

An improved sparsity estimation variable step-sizematching pursuit algorithm

Author(s):

Zhang Ruoyu;  Zhao Honglin

Communication Research Center, Harbin Institute of Technology, Harbin 150080, China

Keywords:

compressed sensing;  sparse signal reconstruction;  matching pursuit;  sparsity estimation

PACS:

TN911.7

DOI:

10.3969/j.issn.1003-7985.2016.02.006

Abstract:

To improve the reconstruction performance of the greedy algorithm for sparse signals, an improved greedy algorithm, called sparsity estimation variable step-size matching pursuit, is proposed. Compared with state-of-the-art greedy algorithms, the proposed algorithm incorporates the restricted isometry property and variable step-size, which is utilized for sparsity estimation and reduces the reconstruction time, respectively. Based on the sparsity estimation, the initial value including sparsity level and support set is computed at the beginning of the reconstruction, which provides preliminary sparsity information for signal reconstruction. Then, the residual and correlation are calculated according to the initial value and the support set is refined at the next iteration associated with variable step-size and backtracking. Finally, the correct support set is obtained when the halting condition is reached and the original signal is reconstructed accurately. The simulation results demonstrate that the proposed algorithm improves the recovery performance and considerably outperforms the existing algorithm in terms of the running time in sparse signal reconstruction.

References:

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Memo

Memo:

Biographies: Zhang Ruoyu(1992—), male, graduate; Zhao Honglin(corresponding author), male, doctor, professor, hlzhao@hit.edu.cn.
Foundation item: The National Basic Research Program of China(973 Program)(No.2013CB329003).
Citation: Zhang Ruoyu, Zhao Honglin. An improved sparsity estimation variable step-size matching pursuit algorithm[J].Journal of Southeast University(English Edition), 2016, 32(2):164-169.doi:10.3969/j.issn.1003-7985.2016.02.006.

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