BlockSparseRecovery_Kuroda-Kitahara.pdf (3.02 MB)
Download file

Block-Sparse Recovery with Optimal Block Partition

Download (3.02 MB)
posted on 2022-03-03, 16:31 authored by Hiroki KurodaHiroki Kuroda, Daichi KitaharaDaichi Kitahara
This paper presents a convex recovery method for block-sparse signals whose block partitions are unknown a priori. We first introduce a nonconvex penalty function, where the block partition is adapted for the signal of interest by minimizing the mixed l2/l1 norm over all possible block partitions. Then, by exploiting a variational representation of the l2 norm, we derive the proposed penalty function as a suitable convex relaxation of the nonconvex one. For a block-sparse recovery model designed with the proposed penalty, we develop an iterative algorithm which is guaranteed to converge to a globally optimal solution. Numerical experiments demonstrate the effectiveness of the proposed method.


Email Address of Submitting Author

ORCID of Submitting Author


Submitting Author's Institution

Ritsumeikan University

Submitting Author's Country

  • Japan