A new preconditioned AOR-type method for M-tensor equation

Zhuling Jiang; Jicheng Li

doi:10.1016/j.apnum.2023.03.013

A new preconditioned AOR-type method for M-tensor equation

Zhuling Jiang
, Jicheng Li

School of Mathematics and Statistics

Xi'an Jiaotong University

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

By using a truncated Neumann series approximation to the inverse of a given matrix, we propose a new preconditioner for improving the AOR-type method, then we develop preconditioned AOR-type methods to solve M-tensor equation and prove that the methods are convergent. Some comparison theorems are provided to show that the preconditioned AOR-type methods perform better than the AOR-type method. Finally, numerical examples illustrate that our methods are feasible and effective.

Original language	English
Pages (from-to)	39-52
Number of pages	14
Journal	Applied Numerical Mathematics
Volume	189
DOIs	https://doi.org/10.1016/j.apnum.2023.03.013
State	Published - Jul 2023

Keywords

Comparison theorems
M-tensor equation
Preconditioned AOR-type methods
Preconditioner

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10.1016/j.apnum.2023.03.013

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title = "A new preconditioned AOR-type method for M-tensor equation",

abstract = "By using a truncated Neumann series approximation to the inverse of a given matrix, we propose a new preconditioner for improving the AOR-type method, then we develop preconditioned AOR-type methods to solve M-tensor equation and prove that the methods are convergent. Some comparison theorems are provided to show that the preconditioned AOR-type methods perform better than the AOR-type method. Finally, numerical examples illustrate that our methods are feasible and effective.",

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author = "Zhuling Jiang and Jicheng Li",

note = "Publisher Copyright: {\textcopyright} 2023 IMACS",

year = "2023",

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AU - Jiang, Zhuling

AU - Li, Jicheng

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N2 - By using a truncated Neumann series approximation to the inverse of a given matrix, we propose a new preconditioner for improving the AOR-type method, then we develop preconditioned AOR-type methods to solve M-tensor equation and prove that the methods are convergent. Some comparison theorems are provided to show that the preconditioned AOR-type methods perform better than the AOR-type method. Finally, numerical examples illustrate that our methods are feasible and effective.

AB - By using a truncated Neumann series approximation to the inverse of a given matrix, we propose a new preconditioner for improving the AOR-type method, then we develop preconditioned AOR-type methods to solve M-tensor equation and prove that the methods are convergent. Some comparison theorems are provided to show that the preconditioned AOR-type methods perform better than the AOR-type method. Finally, numerical examples illustrate that our methods are feasible and effective.

KW - Comparison theorems

KW - M-tensor equation

KW - Preconditioned AOR-type methods

KW - Preconditioner

UR - https://www.scopus.com/pages/publications/85151557922

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DO - 10.1016/j.apnum.2023.03.013

M3 - 文章

AN - SCOPUS:85151557922

SN - 0168-9274

VL - 189

SP - 39

EP - 52

JO - Applied Numerical Mathematics

JF - Applied Numerical Mathematics

ER -

A new preconditioned AOR-type method for M-tensor equation

Abstract

Keywords

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