@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 = {<p style="text-align: justify;">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.</p>},
issn = {2079-7338},
doi = {https://doi.org/10.4208/nmtma.2016.m1428},
url = {http://global-sci.org/intro/article_detail/nmtma/12372.html}
}