Computing the singular value decompostion of a product of two matrices
SIAM Journal on Scientific and Statistical Computing
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Least Squares Solution of BXAT=T over Symmetric, Skew-Symmetric, and Positive Semidefinite X
SIAM Journal on Matrix Analysis and Applications
Iterative solutions to matrix equations of the form AiXBi=Fi
Computers & Mathematics with Applications
On Hermitian and skew-Hermitian splitting iteration methods for the linear matrix equation AXB=C
Computers & Mathematics with Applications
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The *congruence class of a least square solution for the following matrix equations AX=B,A^*XA=D,AXB=Dand(AXXB)=(EF) is presented. Also, we derive necessary and sufficient conditions for the existence of a least square solution and present a general form of such solutions using the Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD).