Compressive sensing with noise based on SCAD penalty

Hai Zhang; Yong Liang; Zong Ben Xu; Xiang Yu Chang

Compressive sensing with noise based on SCAD penalty

Hai Zhang
, Yong Liang
, Zong Ben Xu
, Xiang Yu Chang

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

We study the compressive sensing with noise. We propose a new strategy for compressive sensing based on SCAD, and we give an efficient thresholding algorithm for solving the new model. The new method is robust to the observation noise. These fundamental properties of the compressive sensing strategy based on SCAD are supported and demonstrated both by simulations and theoretical results.

Original language	English
Pages (from-to)	767-776
Number of pages	10
Journal	Acta Mathematica Sinica, Chinese Series
Volume	56
Issue number	5
State	Published - Sep 2013

Keywords

Compressive sensing
Regularization
Sparsity

Cite this

@article{ecececb120df4e5faefa9e4bc2bac9c3,

title = "Compressive sensing with noise based on SCAD penalty",

abstract = "We study the compressive sensing with noise. We propose a new strategy for compressive sensing based on SCAD, and we give an efficient thresholding algorithm for solving the new model. The new method is robust to the observation noise. These fundamental properties of the compressive sensing strategy based on SCAD are supported and demonstrated both by simulations and theoretical results.",

keywords = "Compressive sensing, Regularization, Sparsity",

author = "Hai Zhang and Yong Liang and Xu, \{Zong Ben\} and Chang, \{Xiang Yu\}",

year = "2013",

month = sep,

language = "英语",

volume = "56",

pages = "767--776",

journal = "Acta Mathematica Sinica, Chinese Series",

issn = "0583-1431",

publisher = "Chinese Academy of Sciences",

number = "5",

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TY - JOUR

T1 - Compressive sensing with noise based on SCAD penalty

AU - Zhang, Hai

AU - Liang, Yong

AU - Xu, Zong Ben

AU - Chang, Xiang Yu

PY - 2013/9

Y1 - 2013/9

N2 - We study the compressive sensing with noise. We propose a new strategy for compressive sensing based on SCAD, and we give an efficient thresholding algorithm for solving the new model. The new method is robust to the observation noise. These fundamental properties of the compressive sensing strategy based on SCAD are supported and demonstrated both by simulations and theoretical results.

AB - We study the compressive sensing with noise. We propose a new strategy for compressive sensing based on SCAD, and we give an efficient thresholding algorithm for solving the new model. The new method is robust to the observation noise. These fundamental properties of the compressive sensing strategy based on SCAD are supported and demonstrated both by simulations and theoretical results.

KW - Compressive sensing

KW - Regularization

KW - Sparsity

UR - https://www.scopus.com/pages/publications/84891861371

M3 - 文章

AN - SCOPUS:84891861371

SN - 0583-1431

VL - 56

SP - 767

EP - 776

JO - Acta Mathematica Sinica, Chinese Series

JF - Acta Mathematica Sinica, Chinese Series

IS - 5

ER -

Compressive sensing with noise based on SCAD penalty

Abstract

Keywords

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