One-Bit Compressed Sensing by Greedy Algorithms. Issue 2 (24th May 2016)

• Record Type: Journal Article
• Authors: Liu, Wenhui; Gong, Da; Xu, Zhiqiang
• Is Part Of: Numerical mathematics. Volume 9:Issue 2(2016)
• Page Start: 169
• Page End: 184
• Publication Date: 2016-05-24
• Subjects: 94A12, -- 65H99, -- 65D15; Compressed sensing, -- sparse signals, -- greedy algorithm; Numerical analysis -- Periodicals; Numerical analysis; Periodicals; 518.05
• DOI: 10.4208/nmtma.2016.m1428
• Languages: English
• ISSNs: 1004-8979

Abstract

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.