Convergence analysis of gradient-based iterative algorithms for a class of rectangular Sylvester matrix equations based on Banach contraction principle

Convergence analysis of gradient-based iterative algorithms for a class of rectangular Sylvester matrix equations based on Banach contraction principle

Abstract We derive an iterative procedure for solving a generalized Sylvester matrix equation A X B + C X D = E $AXB+CXD = E$ , where A , B , C , D , E $A,B,C,D,E$ are conforming rectangular matrices. Our algorithm is based on gradients and hierarchical identification principle. We convert the matri...

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Bibliographic Details
Main Authors: Adisorn Kittisopaporn, Pattrawut Chansangiam, Wicharn Lewkeeratiyutkul
Format: Article
Language:English
Published: SpringerOpen 2021-01-01
Series:Advances in Difference Equations
Subjects:
Generalized Sylvester matrix equation
Gradient
Linear difference vector equation
Banach contraction principle
Kronecker product
Matrix norms
Online Access:https://doi.org/10.1186/s13662-020-03185-9

Internet

https://doi.org/10.1186/s13662-020-03185-9

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