paper

Sharp Sufficient Conditions for Stable Recovery of Block Sparse Signals by Block Orthogonal Matching Pursuit

arXiv:1605.02894

Abstract

In this paper, we use the block orthogonal matching pursuit (BOMP) algorithm to recover block sparse signals $\x$ from measurements $\y=\A\x+\v$, where $\v$ is an -bounded noise vector (i.e., for some constant ). We investigate some sufficient conditions based on the block restricted isometry property (block-RIP) for exact (when $\v=\0$) and stable (when $\v\neq\0$) recovery of block sparse signals $\x$. First, on the one hand, we show that if $\A$ satisfies the block-RIP with , then every block -sparse signal $\x$ can be exactly or stably recovered by BOMP in iterations. On the other hand, we show that, for any and , there exists a matrix $\A$ satisfying the block-RIP with and a block -sparse signal $\x$ such that BOMP may fail to recover $\x$ in iterations. Then, we study some sufficient conditions for recovering block -strongly-decaying -sparse signals. We show that if $\A$ satisfies the block-RIP with , then every -strongly-decaying block -sparse signal can be exactly or stably recovered by BOMP in iterations under some conditions on . Our newly found sufficient condition on the block-RIP of $\A$ is less restrictive than that for minimization for this special class of sparse signals. Furthermore, for any , and , the recovery of $\x$ may fail in iterations for a sensing matrix $\A$ which satisfies the block-RIP with . Finally, we study some sufficient conditions for partial recovery of block sparse signals. Specifically, if $\A$ satisfies the block-RIP with , then BOMP is guaranteed to recover some blocks of $\x$ if these blocks satisfy a sufficient condition.

to appear in Applied and Computational Harmonic Analysis, https://doi.org/10.1016/j.acha.2018.02.002

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