Parallel algorithms for large least squares problems involving Kronecker products
Nonlinear Analysis: Theory, Methods & Applications
Perturbation bound of singular linear systems
Applied Mathematics and Computation
The representation and approximation for Drazin inverse
Journal of Computational and Applied Mathematics
Recurrent neural networks for computing weighted Moore-Penrose inverse
Applied Mathematics and Computation
Applied Mathematics and Computation
Integral representation of the W-weighted Drazin inverse
Applied Mathematics and Computation
Weighted least squares solutions to general coupled Sylvester matrix equations
Journal of Computational and Applied Mathematics
Gradient based iterative solutions for general linear matrix equations
Computers & Mathematics with Applications
Gradient-based iterative solutions for general matrix equations
ACC'09 Proceedings of the 2009 conference on American Control Conference
Transformations between some special matrices
Computers & Mathematics with Applications
Iterative solutions to coupled Sylvester-conjugate matrix equations
Computers & Mathematics with Applications
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The weighted least-squares solutions of coupled singular matrix equations are too difficult to obtain by applying matrices decomposition. In this paper, a family of algorithms are applied to solve these problems based on the Kronecker structures. Subsequently, we construct a computationally efficient solutions of coupled restricted singular matrix equations. Furthermore, the need to compute the weighted Drazin and weighted Moore-Penrose inverses; and the use of Tian's work and Lev-Ari's results are due to appearance in the solutions of these problems. The several special cases of these problems are also considered which includes the well-known coupled Sylvester matrix equations. Finally, we recover the iterative methods to the weighted case in order to obtain the minimum D-norm G-vector least-squares solutions for the coupled Sylvester matrix equations and the results lead to the least-squares solutions and invertible solutions, as a special case.