Sparse Signals Recovery from Noisy Measurements by Orthogonal Matching Pursuit

2011/05/31 by Shen, Yi, Li, Song
#FOS: Mathematics #Functional Analysis (math.FA)

paper · doi:10.48550/arxiv.1105.6177

Abstract

Recently, many practical algorithms have been proposed to recover the sparse signal from fewer measurements. Orthogonal matching pursuit (OMP) is one of the most effective algorithm. In this paper, we use the restricted isometry property to analysis the algorithm. We show that, under certain conditions based on the restricted isometry property and the signals, OMP will recover the support of the sparse signal when measurements are corrupted by additive noise.

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