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Journal of Applied Mathematics and Computing
Erschienen in: Journal of Applied Mathematics and Computing 1-2/2019

12.10.2018 | Original Research

The conjugate gradient methods for solving the generalized periodic Sylvester matrix equations

verfasst von: Min Sun, Yiju Wang

Erschienen in: Journal of Applied Mathematics and Computing | Ausgabe 1-2/2019

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Abstract

This work is devoted to designing two conjugate gradient methods for the least Frobenius norm solution of the generalized periodic Sylvester matrix equations. When the studied problem is consistent, the first conjugate gradient method can find its solution within finite iterative steps in the absence of round-off errors. Furthermore, its least Frobenius norm solution can be obtained with some special kind of initial matrices. When the studied problem is inconsistent, the second conjugate gradient method with some special kind of initial matrices can find its least squares solution with the least Frobenius norm within finite iterative steps in the absence of round-off errors. Finally, several numerical examples are tested to validate the performance of the proposed methods.
Vorheriger Artikel Fractional optimal control of an HIV/AIDS epidemic model with random testing and contact tracing
Nächster Artikel Extended Newton-type iteration for nonlinear ill-posed equations in Banach space

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Metadaten
Titel
The conjugate gradient methods for solving the generalized periodic Sylvester matrix equations
verfasst von
Min Sun
Yiju Wang
Publikationsdatum
12.10.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Applied Mathematics and Computing / Ausgabe 1-2/2019
Print ISSN: 1598-5865
Elektronische ISSN: 1865-2085
DOI
https://doi.org/10.1007/s12190-018-01220-3

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