中文版 | English
Title

AN ADAPTIVE l(1)-l(2)-TYPE MODEL WITH HIERARCHIES FOR SPARSE SIGNAL RECONSTRUCTION PROBLEM

Author
Corresponding AuthorZhang, Haibin
Publication Years
2022
Source Title
ISSN
1348-9151
Volume18Issue:4
Abstract
This paper addresses solving an adaptive l(1)-l(2) regularized model in the framework of hierarchical convex optimization for sparse signal reconstruction. This is realized in the framework of bi-level convex optimization, we can also turn the challenging bi-level model into a single-level constrained optimization problem through some priori information. The l(1)-l(2 )norm regularized least-square sparse optimization is also called the elastic net problem, and numerous simulation and real-world data show that the elastic net often outperforms the Lasso. However, the elastic net is suitable for handling Gaussian noise in most cases. In this paper, we propose an adaptive and robust model for reconstructing sparse signals, say l(p-)l(1)-l(2), where the l(p)-norm with p >= 1 measures the data fidelity and l(1)-l(2)-term measures the sparsity. This model is robust and flexible in the sense of having the ability to deal with different types of noises. To solve this model, we employ an alternating direction method of multipliers (ADMM) based on introducing one or a pair of auxiliary variables. From the point of view of numerical computation, we use numerical experiments to demonstrate that both of our proposed model and algorithms outperform the Lasso model solved by ADMM on sparse signal reconstruction problem.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Others
WOS Research Area
Operations Research & Management Science ; Mathematics
WOS Subject
Operations Research & Management Science ; Mathematics, Applied
WOS Accession No
WOS:000885435300003
Publisher
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/417046
DepartmentDepartment of Mathematics
Affiliation
1.Beijing Univ Technol, Dept Operat Res & Informat Engn, Beijing 100124, Peoples R China
2.Southern Univ Sci & Technol, Dept Math, Shenzhen 518055, Peoples R China
Recommended Citation
GB/T 7714
Ding, Yanyun,Yue, Zhixiao,Zhang, Haibin. AN ADAPTIVE l(1)-l(2)-TYPE MODEL WITH HIERARCHIES FOR SPARSE SIGNAL RECONSTRUCTION PROBLEM[J]. Pacific Journal of Optimization,2022,18(4).
APA
Ding, Yanyun,Yue, Zhixiao,&Zhang, Haibin.(2022).AN ADAPTIVE l(1)-l(2)-TYPE MODEL WITH HIERARCHIES FOR SPARSE SIGNAL RECONSTRUCTION PROBLEM.Pacific Journal of Optimization,18(4).
MLA
Ding, Yanyun,et al."AN ADAPTIVE l(1)-l(2)-TYPE MODEL WITH HIERARCHIES FOR SPARSE SIGNAL RECONSTRUCTION PROBLEM".Pacific Journal of Optimization 18.4(2022).
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