Conjugate gradient algorithm for consistent generalized Sylvester-transpose matrix equations - Kanjanaporn Tansri; Sarawanee Choomklang; Pattrawut Chansangiam (AIMS Mathematics, 2022)
We develop an effective algorithm to find a well-approximate solution of a generalized Sylvester-transpose matrix equation where all coefficient matrices and an unknown matrix are rectangular. The algorithm aims to construct a finite sequence of approximated solutions from any given initial matrix. It turns out that the associated residual matrices are orthogonal, and thus, the desire solution comes out in the final step with a satisfactory error. We provide numerical experiments to show the capability and performance of the algorithm.
Keywords: Matrix Theory and Algorithms; Advanced Optimization Algorithms Research; Control Systems and Identification