Strictly contractive Peaceman–Rachford splitting method to recover the corrupted low rank matrix

Journal of Inequalities and Applications

Zhiyong Zhang¹  Zheng-Fen Jin²  Zhongping Wan³ 

[1] 0000 0000 9797 0900, grid.453074.1, Information Engineering College, Henan University of Science and Technology, Luoyang, P.R. China;0000 0000 9797 0900, grid.453074.1, School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, China;0000 0001 2331 6153, grid.49470.3e, School of Mathematics and Statistics, Wuhan University, Wuhan, P.R. China;

关键词: Low rank matrix;    Strictly contractive Peaceman–Rachford splitting method;    Nuclear norm minimization;    90C25;    90C06;    90C90;   

DOI  :  10.1186/s13660-019-2091-x

来源: publisher

【 摘 要 】

The strictly contractive Peaceman–Rachford splitting method (SC-PRSM) attracts much attention on solving the separable convex programming. In this paper, the SC-PRSM is first applied to recover the corrupted low rank matrix, which extends the application of the SC-PRSM. At each iteration, we just solve two easy subproblems, where one subproblem has a closed solution and another needs to solve linear equations by the conjugate gradient method. Finally, numerical comparisons with the existing types of the alternating direction method of multipliers show that the SC-PRSM is efficient and competitive for recovering the low rank matrix problems.

【 授权许可】

CC BY