Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4598636 | Linear Algebra and its Applications | 2016 | 28 Pages |
Abstract
Golub and Meurant have shown how to use the symmetric block Lanczos algorithm to compute block Gauss quadrature rules for the approximation of certain matrix functions. We describe new block quadrature rules that can be computed by the symmetric or nonsymmetric block Lanczos algorithms and yield higher accuracy than standard block Gauss rules after the same number of steps of the symmetric or nonsymmetric block Lanczos algorithms. The new rules are block generalizations of the generalized averaged Gauss rules introduced by SpaleviÄ. Applications to network analysis are presented.
Related Topics
Physical Sciences and Engineering
Mathematics
Algebra and Number Theory
Authors
Lothar Reichel, Giuseppe Rodriguez, Tunan Tang,