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A Two Stage Generalized Block Orthogonal Matching Pursuit (TSGBOMP) Algorithm
IEEE Transactions on Signal Processing ( IF 5.4 ) Pub Date : 2021-09-24 , DOI: 10.1109/tsp.2021.3114977
Samrat Mukhopadhyay , Mrityunjoy Chakraborty

Recovery of an unknown sparse signal from a few of its projections is the key objective of compressed sensing. Often one comes across signals that are not ordinarily sparse but are sparse blockwise. Existing block sparse recovery algorithms like BOMP make the assumption of uniform block size and known block boundaries, which are, however, not very practical in many applications. This paper addresses this problem and proposes a two step procedure, where the first stage is a coarse block location identification stage while the second stage carries out finer localization of a non-zero cluster within the window selected in the first stage. A detailed convergence analysis of the proposed algorithm is carried out by first defining a so-called pseudoblock-interleaved block RIP for the given generalized block sparse signal and then imposing upper bounds on the corresponding RIC. Simulation results confirm significantly improved performance of the proposed algorithm as compared to BOMP.

中文翻译:

两阶段广义块正交匹配追踪 (TSGBOMP) 算法

从几个投影中恢复未知的稀疏信号是压缩感知的关键目标。人们经常会遇到通常不稀疏但块状稀疏的信号。现有的块稀疏恢复算法(如 BOMP)假设块大小一致且块边界已知,然而,这在许多应用中并不是很实用。本文解决了这个问题并提出了一个两步程序,其中第一阶段是粗块位置识别阶段,而第二阶段在第一阶段选择的窗口内对非零簇进行更精细的定位。通过首先为给定的广义块稀疏信号定义所谓的伪块交织块 RIP,然后在相应的 RIC 上施加上限,对所提出的算法进行详细的收敛分析。仿真结果证实,与 BOMP 相比,所提出算法的性能显着提高。
更新日期:2021-11-09
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