An Improved Two‐Step Method for Inverse Eigenvalue Problems

ABSTRACT In this article, we investigate the numerical solutions of the inverse eigenvalue problem (IEP). Motivated by the techniques of Aishima in 2018, we propose here an improved two‐step method for the IEP. Compared with other existing methods, the proposed method has higher convergence order and/or requires less operations. Under the assumption that the relative generalized Jacobian matrices at a solution are nonsingular, the proposed method is proved to be convergent with cubic root‐convergence rate. Numerical examples demonstrate the effectiveness of the improved method.

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Publication Details

Journal
Numerical Linear Algebra with Applications
Published
2024-10-23
DOI
https://doi.org/10.1002/nla.2590
Citations
1
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.36

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article

An Improved Two‐Step Method for Inverse Eigenvalue Problems

Enping Lou, Rui Guo, Xiaoguang Yang, Weiping Shen
1 citations
Numerical Linear Algebra with Applications
Matrix Theory and Algorithms
0.36
article

An Improved Two‐Step Method for Inverse Eigenvalue Problems

Enping Lou, Rui Guo, Xiaoguang Yang, Weiping Shen
article en
1 citations

Abstract

ABSTRACT In this article, we investigate the numerical solutions of the inverse eigenvalue problem (IEP). Motivated by the techniques of Aishima in 2018, we propose here an improved two‐step method for the IEP. Compared with other existing methods, the proposed method has higher convergence order and/or requires less operations. Under the assumption that the relative generalized Jacobian matrices at a solution are nonsingular, the proposed method is proved to be convergent with cubic root‐convergence rate. Numerical examples demonstrate the effectiveness of the improved method.

Numerical Linear Algebra with ApplicationsVol. 32(1)
Zhejiang Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 35%
Matrix Theory and Algorithms
0.36
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