Piecewise Sparse Recovery via Piecewise Inverse Scale Space Algorithm with Deletion Rule

Authors

  • Yijun Zhong School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China
  • Chongjun Li School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China

DOI:

https://doi.org/10.4208/jcm.1810-m2017-0233

Keywords:

Inverse scale space, Piecewise sparse, Sparse recovery, Small-scaled entries.

Abstract

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.

Published

2020-02-20

Issue

Section

Articles