PARAMETERIZED REGULARIZED DPSS PRECONDITIONERS FOR NON-HERMITIAN SADDLE POINT PROBLEMS

Recently, Cao [Applied Mathematics Letters, 2018, 84: 96-102] presented a regularized deteriorated positive and skew-Hermitian splitting (RDPSS) iteration method for solving the large sparse non-Hermitian saddle point problems and studied the convergence of the corresponding RDPSS stationary iteration method. In this paper, based on the RDPSS iteration method, we construct a parameterized RDPSS (PRDPSS) iteration method for solving the large sparse non-Hermitian saddle point problems and theoretically prove that presented method converges to the unique solution of the system of linear equations unconditionally. Finally, one example is provided to confirm the effectiveness.