TY - JOUR
T1 - Piecewise Sparse Recovery via Piecewise Inverse Scale Space Algorithm with Deletion Rule
AU - Zhong , Yijun
AU - Li , Chongjun
JO - Journal of Computational Mathematics
VL - 2
SP - 375
EP - 394
PY - 2020
DA - 2020/02
SN - 38
DO - http://doi.org/10.4208/jcm.1810-m2017-0233
UR - https://global-sci.org/intro/article_detail/jcm/14522.html
KW - Inverse scale space, Piecewise sparse, Sparse recovery, Small-scaled entries.
AB - <p style="text-align: justify;">In some applications, there are signals with piecewise structure to be recovered. In this
paper, we propose a piecewise_ISS (P_ISS) method which aims to preserve the piecewise
sparse structure (or the small-scaled entries) of piecewise signals. In order to avoid selecting
redundant false small-scaled elements, we also implement the piecewise_ISS algorithm in
parallel and distributed manners equipped with a deletion rule. Numerical experiments
indicate that compared with aISS, the P_ISS algorithm is more effective and robust for
piecewise sparse recovery.</p>