On Iterative Solutions of General Coupled Matrix Equations
SIAM Journal on Control and Optimization
Ranks of least squares solutions of the matrix equation AXB=C
Computers & Mathematics with Applications
The residual based extended least squares identification method for dual-rate systems
Computers & Mathematics with Applications
Computers & Mathematics with Applications
Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems
Computers & Mathematics with Applications
Weighted least squares solutions to general coupled Sylvester matrix equations
Journal of Computational and Applied Mathematics
The *congruence class of the solutions of some matrix equations
Computers & Mathematics with Applications
Gradient based iterative solutions for general linear matrix equations
Computers & Mathematics with Applications
Least-squares solution with the minimum-norm for the matrix equation (AXB, GXH) = (C, D)
Computers & Mathematics with Applications
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I
Computers & Mathematics with Applications
Identification methods for Hammerstein nonlinear systems
Digital Signal Processing
Some properties of inverses of the full matrices
Computers & Mathematics with Applications
Computers & Mathematics with Applications
Observable state space realizations for multivariable systems
Computers & Mathematics with Applications
Mathematical and Computer Modelling: An International Journal
Identification for the second-order systems based on the step response
Mathematical and Computer Modelling: An International Journal
Developing Bi-CG and Bi-CR methods to solve generalized Sylvester-transpose matrix equations
International Journal of Automation and Computing
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This paper is concerned with the numerical solutions to the linear matrix equations A"1XB"1=F"1 and A"2XB"2=F"2; two iterative algorithms are presented to obtain the solutions. For any initial value, it is proved that the iterative solutions obtained by the proposed algorithms converge to their true values. Finally, simulation examples are given to verify the proposed convergence theorems.