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论文类型： 期刊论文

发表时间： 2018-03-15

发表刊物： JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

收录刊物： SCIE、EI、ESI高被引论文

卷号： 331

页面范围： 166-177

ISSN号： 0377-0427

关键字： Shifted linear system; Hessenberg process; Pivoting strategy; Restarted Hessenberg method; Collinear; Fractional differential equations

摘要： It is known that the restarted full orthogonalization method (FOM) outperforms the restarted generalized minimum residual (GMRES) method in several circumstances for solving shifted linear systems when the shifts are handled simultaneously. Many variants of them have been proposed to enhance their performance. We show that another restarted method, the restarted Hessenberg method (Heyouni, 1996) based on Hessenberg procedure, can effectively be employed, which can provide accelerating convergence rate with respect to the number of restarts. Theoretical analysis shows that the new residual of shifted restarted Hessenberg method is still collinear with each other. In these cases where the proposed algorithm needs less enough elapsed CPU time to converge than the earlier established restarted shifted FOM, the weighted restarted shifted FOM, and some other popular shifted iterative solvers based on the short-term vector recurrence, as shown via extensive numerical experiments involving the recently popular application of handling time fractional differential equations. (C) 2017 Elsevier B.V. All rights reserved.