Solving the system of nonsingular tensor equations via randomized Kaczmarz-like method

A great deal of attention has been paid to solve the system of tensor equations in recent years for its applications in various fields. In this paper, the Kaczmarz-like method, which is an effective approach for solving linear equations, is considered to deal with the system of tensor equations with...

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Veröffentlicht in:Journal of computational and applied mathematics Jg. 421; S. 114856
Hauptverfasser: Wang, Xuezhong, Che, Maolin, Mo, Changxin, Wei, Yimin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 15.03.2023
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ISSN:0377-0427, 1879-1778
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Abstract A great deal of attention has been paid to solve the system of tensor equations in recent years for its applications in various fields. In this paper, the Kaczmarz-like method, which is an effective approach for solving linear equations, is considered to deal with the system of tensor equations with nonsingular coefficient tensors. To reach this goal, two algorithms, i.e., the randomized Kaczmarz-like algorithm and its relaxed version, are proposed. The convergence analysis of these two approaches are given based on matrix SVD and the local tangential cone condition. Moreover, we present estimations of the convergence rate. Several numerical examples are presented to validate the theoretical results and reliability as well as effectiveness.
AbstractList A great deal of attention has been paid to solve the system of tensor equations in recent years for its applications in various fields. In this paper, the Kaczmarz-like method, which is an effective approach for solving linear equations, is considered to deal with the system of tensor equations with nonsingular coefficient tensors. To reach this goal, two algorithms, i.e., the randomized Kaczmarz-like algorithm and its relaxed version, are proposed. The convergence analysis of these two approaches are given based on matrix SVD and the local tangential cone condition. Moreover, we present estimations of the convergence rate. Several numerical examples are presented to validate the theoretical results and reliability as well as effectiveness.
ArticleNumber 114856
Author Che, Maolin
Wang, Xuezhong
Wei, Yimin
Mo, Changxin
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  surname: Wang
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  organization: School of Mathematics and Statistics, Hexi University, Zhangye, 734000, PR China
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  givenname: Maolin
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  email: cheml@swufe.edu.cn
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  givenname: Changxin
  surname: Mo
  fullname: Mo, Changxin
  email: cxmo16@cqnu.edu.cn
  organization: School of Mathematical Sciences, Chongqing Normal University, Chongqing, 401331, PR China
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  givenname: Yimin
  orcidid: 0000-0001-6192-0546
  surname: Wei
  fullname: Wei, Yimin
  email: ymwei@fudan.edu.cn
  organization: School of Mathematical Sciences and Key Laboratory of Mathematics for Nonlinear Sciences, Fudan University, Shanghai, 200433, PR China
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Keywords 65C20
Kaczmarz method
Convergence rate
15A69
Randomized algorithm
65J15
The system of tensor equations
Convergence analysis
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Snippet A great deal of attention has been paid to solve the system of tensor equations in recent years for its applications in various fields. In this paper, the...
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StartPage 114856
SubjectTerms Convergence analysis
Convergence rate
Kaczmarz method
Randomized algorithm
The system of tensor equations
Title Solving the system of nonsingular tensor equations via randomized Kaczmarz-like method
URI https://dx.doi.org/10.1016/j.cam.2022.114856
Volume 421
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