Two new preconditioned GAOR methods for weighted linear least squares problems

In this paper, the preconditioned generalized accelerated overrelaxation (GAOR) methods for solving weighted linear least squares problems are considered. Two new preconditioners are proposed and the convergence rates of the new preconditioned GAOR methods are studied. Comparison results show that the convergence rates of the new preconditioned GAOR methods are better than those of the preconditioned GAOR methods in the previous literatures whenever these methods are convergent. A numerical example is given to confirm our theoretical results.