A modified PRP conjugate gradient method with inertial extrapolation for sparse signal reconstruction

It is widely known that the inertial technique of the heavy-ball method can accelerate its convergence speed. In this paper, by embedding the inertial technique in the famous PRP conjugate gradient method, we propose a modified PRP conjugate gradient method with inertial extrapolation (PRPCG-IE) for sparse signal reconstruction. Its direction satisfies the sufficient descent property, which is independent of any line search. Global convergence of PRPCG-IE is established under some standard conditions. PRPCG-IE is applied to two sparse signal reconstruction problems with noise, and preliminary experimental results demonstrate the effectiveness of PRPCG-IE.

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Publication Details

Journal
Journal of Inequalities and Applications
Published
2024-11-06
DOI
https://doi.org/10.1186/s13660-024-03219-w
Citations
1
Primary Topic
Sparse and Compressive Sensing Techniques
Type
article
Field-Weighted Citation Impact
0.37

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article

A modified PRP conjugate gradient method with inertial extrapolation for sparse signal reconstruction

Yuanshou Zhang, Jing Liu, Min Sun
1 citations
Journal of Inequalities and Applications
Sparse and Compressive Sensing Techniques
0.37
article

A modified PRP conjugate gradient method with inertial extrapolation for sparse signal reconstruction

Yuanshou Zhang, Jing Liu, Min Sun
article en
1 citations

Abstract

It is widely known that the inertial technique of the heavy-ball method can accelerate its convergence speed. In this paper, by embedding the inertial technique in the famous PRP conjugate gradient method, we propose a modified PRP conjugate gradient method with inertial extrapolation (PRPCG-IE) for sparse signal reconstruction. Its direction satisfies the sufficient descent property, which is independent of any line search. Global convergence of PRPCG-IE is established under some standard conditions. PRPCG-IE is applied to two sparse signal reconstruction problems with noise, and preliminary experimental results demonstrate the effectiveness of PRPCG-IE.

Journal of Inequalities and ApplicationsVol. 2024(1)
Zaozhuang University (CN), Weifang University (CN), Zhejiang University of Finance and Economics (CN)
Natural Science Foundation of Shandong Province
Climate action
Openalex Percentile: Top 41%
Sparse and Compressive Sensing Techniques
0.37
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A modified PRP conjugate gradient method with inertial extrapolation for sparse signal reconstruction — Yuanshou Zhang, Jing Liu, et al. · Journal of Inequalities and Applications (2024) | TGRS Research Map | TGRS