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The Weighted, Relaxed Gradient-Based Iterative Algorithm for the Generalized Coupled Conjugate and Transpose Sylvester Matrix Equations

Authors :
Xiaowen Wu
Zhengge Huang
Jingjing Cui
Yanping Long
Source :
Axioms, Vol 12, Iss 11, p 1062 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

By applying the weighted relaxation technique to the gradient-based iterative (GI) algorithm and taking proper weighted combinations of the solutions, this paper proposes the weighted, relaxed gradient-based iterative (WRGI) algorithm to solve the generalized coupled conjugate and transpose Sylvester matrix equations. With the real representation of a complex matrix as a tool, the necessary and sufficient conditions for the convergence of the WRGI algorithm are determined. Also, some sufficient convergence conditions of the WRGI algorithm are presented. Moreover, the optimal step size and the corresponding optimal convergence factor of the WRGI algorithm are given. Lastly, some numerical examples are provided to demonstrate the effectiveness, feasibility and superiority of the proposed algorithm.

Details

Language :
English
ISSN :
20751680
Volume :
12
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Axioms
Publication Type :
Academic Journal
Accession number :
edsdoj.23f18ae884c24bef8adb22bac2204e76
Document Type :
article
Full Text :
https://doi.org/10.3390/axioms12111062