Paper Info
Title
Restarted weighted full orthogonalization method for shifted linear systems
Abstract
It is known that the restarted full orthogonalization method (FOM) outperforms the restarted generalized minimum residual method (GMRES) in several circumstances for solving shifted linear systems when the shifts are handled simultaneously. On the basis of the Weighted Arnoldi process, a weighted version of the Restarted Shifted FOM is proposed, which can provide accelerating convergence rate with respect to the number of restarts. In the cases where our hybrid algorithm needs less enough number of restarts to converge than the Restarted Shifted FOM, the associated CPU consuming time is also reduced, as shown by the numerical experiments. Moreover, our algorithm is able to solve certain shifted systems which the Restarted Shifted FOM cannot handle sometimes.
Year
DOI
Venue
2009
10.1016/j.camwa.2008.10.088
Computers & Mathematics with Applications
Keywords
Field
DocType
restarted fom,full orthogonalization method,shifted algebraic linear system,arnoldi process,restarted shifted fom,hybrid algorithm,restarted weighted full orthogonalization,enough number,numerical experiment,cpu consuming time,linear system,accelerating convergence rate,convergence rate,minimum residual method,weighted arnoldi process
Residual,Mathematical optimization,Hybrid algorithm,Generalized minimal residual method,Linear system,Algorithm,Rate of convergence,Orthogonalization,Mathematics
Journal
Volume
Issue
ISSN
57
9
Computers and Mathematics with Applications
Citations 
PageRank 
References 
11
0.56
15
Authors
2
Name
Order
Citations
PageRank
Yan-Fei Jing1679.48
Ting-Zhu Huang2851101.81