Recovery Performance of IHT and HTP Algorithms under General Perturbations

Xiaobo ZHANG; Wenbo XU; Yupeng CUI; Jiaru LIN

doi:10.1587/transfun.E101.A.1698

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Recovery Performance of IHT and HTP Algorithms under General Perturbations

Xiaobo ZHANG, Wenbo XU, Yupeng CUI, Jiaru LIN

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Keywords: compressed sensing, matrix perturbation, IHT algorithm, HTP algorithm, restricted isometry property

JOURNAL RESTRICTED ACCESS

2018 Volume E101.A Issue 10 Pages 1698-1702

DOI https://doi.org/10.1587/transfun.E101.A.1698

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Abstract

In compressed sensing, most previous researches have studied the recovery performance of a sparse signal x based on the acquired model y=Φx+n, where n denotes the noise vector. There are also related studies for general perturbation environment, i.e., y=(Φ+E)x+n, where E is the measurement perturbation. IHT and HTP algorithms are the classical algorithms for sparse signal reconstruction in compressed sensing. Under the general perturbations, this paper derive the required sufficient conditions and the error bounds of IHT and HTP algorithms.

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