Least-squares solution with the minimum-norm for the matrix equation (AXB, GXH) = (C, D)-Reference-Cited by-同舟云学术

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Least-squares solution with the minimum-norm for the matrix equation (AXB, GXH) = (C, D)

Published:2005-08 Issue:3-4 Volume:50 Page:539-549
ISSN:0898-1221
Container-title:Computers & Mathematics with Applications
language:en
Short-container-title:Computers & Mathematics with Applications

Author:

Liao An-Ping,Lei Yuan

Publisher

Elsevier BV

Subject

Computational Mathematics,Computational Theory and Mathematics,Modelling and Simulation

Reference21 articles.

1. Linear matrix equations and pole assignment;Kolka,1984

2. Feedback decoupling and stabilization for linear system with multiple exogenous variables;Woude,1987

3. Common solutions to a pair of linear matrix equations A1XB1 = C1 and A2XB2 = C2;Mitra,1973

4. Singular value and generalized singular value decomposition and the solution of linear matrix equation;Chu;Linear Algebra Appl.,1987

5. A generalization of a class of inverse eigenvalue problem;Liao;J. Hunan Univ.,1995

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1. Numerical strategies for recursive least squares solutions to the matrix equation AX = B;International Journal of Computer Mathematics;2022-10-21

2. A real representation method for special least squares solutions of the quaternion matrix equation $ (AXB, DXE) = (C, F) $;AIMS Mathematics;2022

3. On the positive definite solution of a class of pair of nonlinear matrix equations;Computational and Applied Mathematics;2020-03-09

4. Submatrix constrained least-squares inverse problem for symmetric matrices from the design of vibrating structures;Journal of Computational and Applied Mathematics;2019-08

5. Numerical algorithms for solving the least squares symmetric problem of matrix equation AXB + CXD = E;Filomat;2019

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