Iterative optimal solutions of linear matrix equations for Hyperspectral and Multispectral image fusing

For a linear matrix function $f$ in $X in R^{mtimes n}$ we consider inhomogeneous linear matrix equations $f(X) = E$ for $E eq 0$ that have or do not have solutions. For such systems we compute optimal norm constrained solutions iteratively using the Conjugate Gradient and Lanczos methods in combination with the More-Sorensen optimizer. We build codes for ten linear matrix equations, of Sylvester, Lyapunov, Stein and structured types and their