A method for eigenvalues of sparse λ-matrices
✍ Scribed by Wei H. Yang
- Publisher
- John Wiley and Sons
- Year
- 1983
- Tongue
- English
- Weight
- 308 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0029-5981
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
The autoadjusting perturbation theory method is presented and developed to calculate eigenpairs of a square matrix. The procedures to simultaneously compute a cluster of eigenpairs by variance minimization are also given. Finally, numerical examples are reported.
Conjugate gradient methods for solving sparse systems of linear equations and Lanczos algorithms for sparse symmetric eigenvalue problems play an important role in numerical methods for solving discretized partial differential equations. When these iterative solvers are parallelized on a multiproces
## Abstract Eigenvalue bounds are provided. It is proved that the minimal eigenvalue of a __Z__‐matrix strictly diagonally dominant with positive diagonals lies between the minimal and the maximal row sums. A similar upper bound does not hold for the minimal eigenvalue of a matrix strictly diagonal