Abstract: In this paper the gradient based iterative algorithm is
presented to solve the linear matrix equation AXB +CXTD = E,
where X is unknown matrix, A,B,C,D,E are the given constant
matrices. It is proved that if the equation has a solution, then the
unique minimum norm solution can be obtained by choosing a special
kind of initial matrices. Two numerical examples show that the
introduced iterative algorithm is quite efficient.
Abstract: In this paper the gradient based iterative algorithms are presented to solve the following four types linear matrix equations: (a) AXB = F; (b) AXB = F, CXD = G; (c) AXB = F s. t. X = XT ; (d) AXB+CYD = F, where X and Y are unknown matrices, A,B,C,D, F,G are the given constant matrices. It is proved that if the equation considered has a solution, then the unique minimum norm solution can be obtained by choosing a special kind of initial matrices. The numerical results show that the proposed method is reliable and attractive.