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Volume 9, Issue 2
One-Bit Compressed Sensing by Greedy Algorithms

Wenhui Liu, Da Gong & Zhiqiang Xu

DOI: 10.4208/nmtma.2016.m1428

Numer. Math. Theor. Meth. Appl., 9 (2016), pp. 169-184.

Published online: 2016-09

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  • Abstract

Sign truncated matching pursuit (STrMP) algorithm is presented in this paper. STrMP is a new greedy algorithm for the recovery of sparse signals from the sign measurement, which combines the principle of consistent reconstruction with orthogonal matching pursuit (OMP). The main part of STrMP is as concise as OMP and hence STrMP is simple to implement. In contrast to previous greedy algorithms for one-bit compressed sensing, STrMP only need to solve a convex and unconstrained subproblem at each iteration. Numerical experiments show that STrMP is fast and accurate for one-bit compressed sensing compared with other algorithms.

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@Article{NMTMA-9-169, author = {Wenhui Liu, Da Gong and Zhiqiang Xu}, title = {One-Bit Compressed Sensing by Greedy Algorithms}, journal = {Numerical Mathematics: Theory, Methods and Applications}, year = {2016}, volume = {9}, number = {2}, pages = {169--184}, abstract = {

Sign truncated matching pursuit (STrMP) algorithm is presented in this paper. STrMP is a new greedy algorithm for the recovery of sparse signals from the sign measurement, which combines the principle of consistent reconstruction with orthogonal matching pursuit (OMP). The main part of STrMP is as concise as OMP and hence STrMP is simple to implement. In contrast to previous greedy algorithms for one-bit compressed sensing, STrMP only need to solve a convex and unconstrained subproblem at each iteration. Numerical experiments show that STrMP is fast and accurate for one-bit compressed sensing compared with other algorithms.

}, issn = {2079-7338}, doi = {https://doi.org/10.4208/nmtma.2016.m1428}, url = {http://global-sci.org/intro/article_detail/nmtma/12372.html} }
TY - JOUR T1 - One-Bit Compressed Sensing by Greedy Algorithms AU - Wenhui Liu, Da Gong & Zhiqiang Xu JO - Numerical Mathematics: Theory, Methods and Applications VL - 2 SP - 169 EP - 184 PY - 2016 DA - 2016/09 SN - 9 DO - http://doi.org/10.4208/nmtma.2016.m1428 UR - https://global-sci.org/intro/article_detail/nmtma/12372.html KW - AB -

Sign truncated matching pursuit (STrMP) algorithm is presented in this paper. STrMP is a new greedy algorithm for the recovery of sparse signals from the sign measurement, which combines the principle of consistent reconstruction with orthogonal matching pursuit (OMP). The main part of STrMP is as concise as OMP and hence STrMP is simple to implement. In contrast to previous greedy algorithms for one-bit compressed sensing, STrMP only need to solve a convex and unconstrained subproblem at each iteration. Numerical experiments show that STrMP is fast and accurate for one-bit compressed sensing compared with other algorithms.

Wenhui Liu, Da Gong and Zhiqiang Xu. (2016). One-Bit Compressed Sensing by Greedy Algorithms. Numerical Mathematics: Theory, Methods and Applications. 9 (2). 169-184. doi:10.4208/nmtma.2016.m1428
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