Least-Squares Solution of $AXB = D$ over Symmetric Positive Semidefinite Matrices $X$

Abstract

Least-squares solution of $AXB = D$ with respect to symmetric positive semidefinite matrix $X$ is considered. By making use of the generalized singular value decomposition, we derive general analytic formulas, and present necessary and sufficient conditions for guaranteeing the existence of the solution. By applying MATLAB 5.2, we give some numerical examples to show the feasibility and accuracy of this construction technique in the finite precision arithmetic.