IMPROVED RELAXED POSITIVE-DEFINITE AND SKEW-HERMITIAN SPLITTING PRECONDITIONERS FOR SADDLE POINT PROBLEMS

作     者：Yang Cao Zhiru Ren Linquan Yao 

作者机构：School of TransportationNantong UniversityNantong 226019China School of Statistics and MathematicsCentral University of Finance and Economics Beijing 100081China School of Urban Rail TransportationSoochow UniversitySuzhou 215006China 

出 版 物：《Journal of Computational Mathematics》 (计算数学（英文）)

年 卷 期：2019年第37卷第1期

页      面：95-111页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：the National Natural Science Foundation of China (Nos.11771225 11301521 11771467 11572210) 

主　　题：Saddle point problems Preconditioning RPSS preconditioner Eigenvalues Krylov subspace method 

摘      要：We establish a class of improved relaxed positive-definite and skew-Hermitian splitting (IRPSS)preconditioners for saddle point *** preconditioners are easier to be implemented than the relaxed positive-definite and skew-Hermitian splitting (RPSS) preconditioner at each step for solving the saddle point *** study spectral properties and the minimal polynomial of the IRPSS preconditioned saddle point matrix.A theoretical optimal IRPSS preconditioner is also obtained,Numerical results show that our proposed IRPSS preconditioners are convergence rate of the GMRES method superior to the existing ones in accelerating the for solving saddle point problems.