Performance analysis of iterative algorithms for sylvester equations

We consider the convergence performance of the iterative algorithms proposed by Ding and Chen for the solution of coupled matrix equations. A stiffness property is given to describe equations where these algorithms converge only very slowly, and a stochastic analysis shows that very slow convergence is a generic feature of these algorithms. Lastly we consider the recently introduced modifications to these algorithms proposed by Zhou et al and discuss their potential to improve the convergence speed for such stiff equations.