A Two‐Step Method for Parameterized Generalized Inverse Eigenvalue Problem

ABSTRACT In this paper, we investigate the numerical solutions of the parameterized generalized inverse eigenvalue problem which is widely applicable in many fields such as structural engineering, mechanics, and physics. Motivated by the iterative procedure for solving general nonlinear equations, we propose here a two‐step method for solving the parameterized generalized inverse eigenvalue problem, which has a higher convergence rate compared with other existing methods. Under some mild conditions, we establish a local convergence result for the proposed method and prove the cubic convergence property. To demonstrate the effectiveness of the proposed method, we present some numerical examples and comparisons with other methods are also made.

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-05-19
DOI
https://doi.org/10.1002/mma.11073
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

A Two‐Step Method for Parameterized Generalized Inverse Eigenvalue Problem

Rui Guo, Xiaoguang Yang, Weiping Shen
Mathematical Methods in the Applied Sciences
Matrix Theory and Algorithms
article

A Two‐Step Method for Parameterized Generalized Inverse Eigenvalue Problem

Rui Guo, Xiaoguang Yang, Weiping Shen
article en

Abstract

ABSTRACT In this paper, we investigate the numerical solutions of the parameterized generalized inverse eigenvalue problem which is widely applicable in many fields such as structural engineering, mechanics, and physics. Motivated by the iterative procedure for solving general nonlinear equations, we propose here a two‐step method for solving the parameterized generalized inverse eigenvalue problem, which has a higher convergence rate compared with other existing methods. Under some mild conditions, we establish a local convergence result for the proposed method and prove the cubic convergence property. To demonstrate the effectiveness of the proposed method, we present some numerical examples and comparisons with other methods are also made.

Mathematical Methods in the Applied SciencesVol. 48(13)
Zhejiang Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
Matrix Theory and Algorithms
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