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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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Summary :

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.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E101-A No.10 pp.1698-1702
Publication Date
2018/10/01
Publicized
Online ISSN
1745-1337
DOI
10.1587/transfun.E101.A.1698
Type of Manuscript
LETTER
Category
Digital Signal Processing

Authors

Xiaobo ZHANG
  Beijing University of Posts and Telecommunications
Wenbo XU
  Beijing University of Posts and Telecommunications
Yupeng CUI
  Beijing University of Posts and Telecommunications
Jiaru LIN
  Beijing University of Posts and Telecommunications

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