Sparse Sylvester Equation Via Alternating Direction Method of Multipliers

Numerous solutions have been investigated or ap-plied for both the Sylvester equation and the sparse Sylvester equation. In this paper, we employ the alternating direction method of multipliers (ADMM) to solve the sparse Sylvester equation, while imposing the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$l_{0}$</tex> norm to the original Sylvester equation formulation. We analyze the iteration scheme for updating each variable and present a corresponding algorithm by extending the classical ADMM. Additionally, several numerical experiments are conducted to validate its feasibility and efficiency.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/ntci64025.2024.10776225
Citations
1
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.36

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article

Sparse Sylvester Equation Via Alternating Direction Method of Multipliers

Lijun Xu, Yijia Zhou, Xueqian Wang
1 citations
Matrix Theory and Algorithms
0.36
article

Sparse Sylvester Equation Via Alternating Direction Method of Multipliers

Lijun Xu, Yijia Zhou, Xueqian Wang
article en
1 citations

Abstract

Numerous solutions have been investigated or ap-plied for both the Sylvester equation and the sparse Sylvester equation. In this paper, we employ the alternating direction method of multipliers (ADMM) to solve the sparse Sylvester equation, while imposing the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$l_{0}$</tex> norm to the original Sylvester equation formulation. We analyze the iteration scheme for updating each variable and present a corresponding algorithm by extending the classical ADMM. Additionally, several numerical experiments are conducted to validate its feasibility and efficiency.

Dalian Neusoft University of Information (CN), Dalian Maritime University (CN)
China Postdoctoral Science Foundation, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 33%
Matrix Theory and Algorithms
0.36
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