Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4639516 | Journal of Computational and Applied Mathematics | 2013 | 11 Pages |
Abstract
A deflated restarting Krylov subspace method for approximating a function of a matrix times a vector is proposed. In contrast to other Krylov subspace methods, the performance of the method in this paper is better. We further show that the deflating algorithm inherits the superlinear convergence property of its unrestarted counterpart for the entire function and present the results of numerical experiments.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Chuanqing Gu, Lin Zheng,