Jiao Fen LI, Xi Yan HU, Lei ZHANG
We discuss the existing relaxed alternating projection method for solving the linear matrix equation AXB=C under some closed convex constraints to X. The considered closed convex constrained set, denoted by R, is (1) the set of bounded matrices, (2) the set of Q-positive definite matrices, (3) the solution set of a linear matrix inequality. We prove the weak convergence of the matrix sequence generated by the proposed algorithm, and present some numerical examples for solving AXB=C under symmetric nonnegative and symmetric positive semidefinite matrices constraint to illustrate the feasibility and efficiency of the proposed algorithm, and to show its clear superiority comparing with alternating projection method and spectral projected gradient method.