A New Smoothed L0 Regularization Approach for Sparse Signal Recovery
Joint Authors
Xiang, Jianhong
Yue, Huihui
Yin, Xiangjun
Wang, Linyu
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-07-17
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Sparse signal reconstruction, as the main link of compressive sensing (CS) theory, has attracted extensive attention in recent years.
The essence of sparse signal reconstruction is how to recover the original signal accurately and effectively from an underdetermined linear system equation (ULSE).
For this problem, we propose a new algorithm called regularization reweighted smoothed L0 norm minimization algorithm, which is simply called RRSL0 algorithm.
Three innovations are made under the framework of this method: (1) a new smoothed function called compound inverse proportional function (CIPF) is proposed; (2) a new reweighted function is proposed; and (3) a mixed conjugate gradient (MCG) method is proposed.
In this algorithm, the reweighted function and the new smoothed function are combined as the sparsity promoting objective, and the constraint condition y-Φx22 is taken as a deviation term.
Both of them constitute an unconstrained optimization problem under the Tikhonov regularization criterion and the MCG method constructed is used to optimize the problem and realize high-precision reconstruction of sparse signals under noise conditions.
Sparse signal recovery experiments on both the simulated and real data show the proposed RRSL0 algorithm performs better than other popular approaches and achieves state-of-the-art performances in signal and image processing.
American Psychological Association (APA)
Xiang, Jianhong& Yue, Huihui& Yin, Xiangjun& Wang, Linyu. 2019. A New Smoothed L0 Regularization Approach for Sparse Signal Recovery. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1194582
Modern Language Association (MLA)
Xiang, Jianhong…[et al.]. A New Smoothed L0 Regularization Approach for Sparse Signal Recovery. Mathematical Problems in Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1194582
American Medical Association (AMA)
Xiang, Jianhong& Yue, Huihui& Yin, Xiangjun& Wang, Linyu. A New Smoothed L0 Regularization Approach for Sparse Signal Recovery. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1194582
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194582