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Ma, Chang-Feng

Publications and source records attributed to Ma, Chang-Feng.

The parameterized preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations

A parameterized preconditioner is proposed for the generalized saddle point problems arising from the incompressible Navier–Stokes equations. The eigenvalues and eigenvectors of the preconditioned matrix are analyzed. Numerical results show that the proposed preconditioner is efficient to accelerate the convergence rate of Krylov subspace methods, such as GMRES method.

97 MATHEMATICS AND COMPUTING↗

A low-order block preconditioner for saddle point linear systems

A preconditioner is proposed for the large and sparse linear saddle point problems, which is based on a low-order three-by-three block saddle point form. The eigenvalue distribution and an upper bound of the degree of the minimal polynomial for the preconditioned matrix are discussed. Numerical results show that the optimal convergence behavior can be achieved when the new preconditioner is used to accelerate the convergence rate of Krylov subspace methods such as GMRES.

97 MATHEMATICS AND COMPUTING↗

A relaxed two-step splitting iteration method for computing PageRank

In this paper, we extend the two-step matrix splitting iteration approach by introducing a new relaxation parameter. The main idea is based on the inner–outer iteration for solving the PageRank problems proposed by Gleich et al. (J Sci Comput 32(1): 349–371, 2010) and Bai (Numer Algebra Cont Optim 2(4): 855–862, 2012) and the two-step splitting iteration presented by Gu et al. (Appl Math Comput 271: 337–343, 2015). The theoretical analysis results show that the proposed method is efficient. Numerical experiments demonstrate that the convergence performances of the method are better than the existing methods.

97 MATHEMATICS AND COMPUTING↗

A new relaxed splitting preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations

Based on the modified relaxed splitting (MRS) preconditioner proposed by Fan and Zhu (Appl Math Lett 55:18–26, 2016), a new relaxed splitting preconditioner is proposed for the generalized saddle point problems arising from the incompressible Navier–Stokes equations. The eigenvalue distribution and an upper bound of the degree of the minimal polynomial of the preconditioned matrix are analyzed. Numerical results show that the proposed preconditioner is superior to the MRS preconditioner when they are used as preconditioners to accelerate the convergence rate of the Krylov subspace methods, such as GMRES.

97 MATHEMATICS AND COMPUTING↗