CONJUGATE GRADIENT METHODS FOR SOLVING THE SMALLEST EIGENPAIR OF LARGE SYMMETRIC EIGENVALUE PROBLEMS
β Scribed by Y. T. FENG; D. R. J. OWEN
- Publisher
- John Wiley and Sons
- Year
- 1996
- Tongue
- English
- Weight
- 1000 KB
- Volume
- 39
- Category
- Article
- ISSN
- 0029-5981
No coin nor oath required. For personal study only.
β¦ Synopsis
In this paper, a detailed description of CG for evaluating eigenvalue problems by minimizing the Rayleigh quotient is presented from both theoretical and computational viewpoints. Three variants of CG together with their asymptotic behaviours and restarted schemes are discussed. In addition, it is shown that with a generally selected preconditioning matrix the actual performance of the PCG scheme may not be superior to an accelerated inverse power method. Finally, some test problems in the finite element simulation of 2-D and 3-D large scale structural models with up to 20200 unknowns are performed to examine and demonstrate the performances.
π SIMILAR VOLUMES
Recently an efficient method (DACG) for the partial solution of the symmetric generalized eigenproblem Ax = Ξ»Bx has been developed, based on the conjugate gradient (CG) minimization of the Rayleigh quotient over successive deflated subspaces of decreasing size. The present paper provides a numerical
A new iterative method based on a Newton correction vector for extension of the Krylov subspace, its diagonal, and band versions are proposed for calculation of selected lowest eigenvalues and corresponding eigenvectors of the generalized symmetric eigenvalue problem. Additionally, diagonal and band
## Abstract This paper illustrates the application of Wynn's vector Ξ΅βalgorithm to solve a system of equations arising in the method of moments (MoM) solution of an electrostatic problem. Since the method is iterative, it does not require inversion of a matrix. The degree of accuracy of the solutio