Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4640712 | Journal of Computational and Applied Mathematics | 2010 | 13 Pages |
Abstract
We discuss a class of deflated block Krylov subspace methods for solving large scale matrix eigenvalue problems. The efficiency of an Arnoldi-type method is examined in computing partial or closely clustered eigenvalues of large matrices. As an improvement, we also propose a refined variant of the Arnoldi-type method. Comparisons show that the refined variant can further improve the Arnoldi-type method and both methods exhibit very regular convergence behavior.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Qiang Niu, Linzhang Lu,