Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13842
Title: Convergence of the reweighted ℓ 1 minimization algorithm for ℓ 2-ℓ p minimization
Authors: Chen, X 
Zhou, W
Keywords: Global convergence
Nonsmooth and nonconvex optimization
Pseudo convex
Stationary points
Issue Date: 2014
Publisher: Springer
Source: Computational optimization and applications, 2014, v. 59, no. 1-2, p. 47-61 How to cite?
Journal: Computational optimization and applications 
Abstract: The iteratively reweighted ℓ 1 minimization algorithm (IRL1) has been widely used for variable selection, signal reconstruction and image processing. In this paper, we show that any sequence generated by the IRL1 is bounded and any accumulation point is a stationary point of the ℓ 2-ℓ p minimization problem with 0<p<1. Moreover, the stationary point is a global minimizer and the convergence rate is approximately linear under certain conditions. We derive posteriori error bounds which can be used to construct practical stopping rules for the algorithm.
URI: http://hdl.handle.net/10397/13842
ISSN: 0926-6003
EISSN: 1573-2894
DOI: 10.1007/s10589-013-9553-8
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

19
Last Week
0
Last month
1
Citations as of Aug 3, 2017

WEB OF SCIENCETM
Citations

17
Last Week
0
Last month
0
Citations as of Aug 15, 2017

Page view(s)

37
Last Week
2
Last month
Checked on Aug 14, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.