Residual norm steepest descent based iterative algorithms for 115 Sylvester tensor equations

Consider the following consistent Sylvester tensor equation X 1 A + X 2 B + X 3 C = D; where the matrices A;B;C and the tensor D are given and X is the un- known tensor. The current paper concerns with examining a simple and neat framework for accelerating the speed of convergence of the gradient- based iterative algorithm and its modied version for solving the mentioned Sylvester tensor equation without setting the restriction of the existence of a unique solution. Numerical experiments are reported which conrm the validity of the presented results.