Recovery analysis for weighted mixed l2/lp minimization with 0 < p ≤ 1

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:352

Article

Zhou, Zhiyong¹  Yu, Jun¹ 

[1] Umea Univ, Dept Math & Math Stat, S-90187 Umea, Sweden

关键词: Compressive sensing;    Prior support information;    Block sparse;    Non-convex minimization;   

DOI  :  10.1016/j.cam.2018.11.031

来源: Elsevier

【 摘 要 】

We study the recovery conditions of weighted mixed l(2)/l(p) (0 < p <= 1) minimization for block sparse signal reconstruction from compressed measurements when partial block support information is available. We show that the block p-restricted isometry property (RIP) can ensure the robust recovery. Moreover, we present the sufficient and necessary condition for the recovery by using weighted block p-null space property. The relationship between the block p-RIP and the weighted block p-null space property has been established. Finally, we illustrate our results with a series of numerical experiments. (C) 2018 Elsevier B.V. All rights reserved.

【 授权许可】

Free