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Research Article | Open Access

Two accelerated gradient-based iteration methods for solving the Sylvester matrix equation AX + XB = C

Huiling Wang1( )Nian-Ci Wu2Yufeng Nie3
College of Applied Mathematics, Shanxi University of Finance and Economics, Taiyuan 030006, China
School of Mathematics and Statistics, South-Central Minzu University, Wuhan 430074, China
School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710072, China
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Abstract

In this paper, combining the precondition technique and momentum item with the gradient-based iteration algorithm, two accelerated iteration algorithms are presented for solving the Sylvester matrix equation AX+XB=C. Sufficient conditions to guarantee the convergence properties of the proposed algorithms are analyzed in detail. Varying the parameters of these algorithms in each iteration, the corresponding adaptive iteration algorithms are also provided, and the adaptive parameters can be explicitly obtained by the minimum residual technique. Several numerical examples are implemented to illustrate the effectiveness of the proposed algorithms.

CLC number: 15A24, 65F30

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AIMS Mathematics
Pages 34734-34752

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Cite this article:
Wang H, Wu N-C, Nie Y. Two accelerated gradient-based iteration methods for solving the Sylvester matrix equation AX + XB = C. AIMS Mathematics, 2024, 9(12): 34734-34752. https://doi.org/10.3934/math.20241654

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Received: 25 September 2024
Revised: 17 November 2024
Accepted: 29 November 2024
Published: 15 December 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)