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 - <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>