@Article{JCM-38-2,
author = {Zhong, Yijun and Li, Chongjun},
title = {Piecewise Sparse Recovery via Piecewise Inverse Scale Space Algorithm with Deletion Rule},
journal = {Journal of Computational Mathematics},
year = {2020},
volume = {38},
number = {2},
pages = {375--394},
abstract = {<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>},
issn = {1991-7139},
doi = {https://doi.org/10.4208/jcm.1810-m2017-0233},
url = {https://global-sci.com/article/84315/piecewise-sparse-recovery-via-piecewise-inverse-scale-space-algorithm-with-deletion-rule}
}