Some Results for Exact Support Recovery of Block Joint Sparse Matrix via Block Multiple Measurement Vectors Algorithm
Some Results for Exact Support Recovery of Block Joint Sparse Matrix via Block Multiple Measurement Vectors Algorithm作者机构：School of Science Chongqing University of Posts and Telecommunications Chongqing China
出 版 物：《Journal of Applied Mathematics and Physics》 (应用数学与应用物理（英文）)
年 卷 期：2023年第11卷第4期
页 面：1098-1112页
学科分类：08[工学] 0823[工学-交通运输工程]
主 题：Support Recovery Compressed Sensing Block Multiple Measurement Vectors Algorithm Block Restricted Isometry Property
摘 要：Block multiple measurement vectors (BMMV) is a reconstruction algorithm that can be used to recover the support of block K-joint sparse matrix X from Y = ΨX + V. In this paper, we propose a sufficient condition for accurate support recovery of the block K-joint sparse matrix via the BMMV algorithm in the noisy case. Furthermore, we show the optimality of the condition we proposed in the absence of noise when the problem reduces to single measurement vector case.
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