A simultaneous coordinate relaxation algorithm for large, sparse matrix eigenvalue problems
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Publication:1146497
DOI10.1016/0021-9991(79)90152-9zbMath0447.65014OpenAlexW1983537157MaRDI QIDQ1146497
Publication date: 1979
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0021-9991(79)90152-9
test matriceslarge, sparse matrix eigenvalue problemsseveral most dominant eigenvectorssimultaneous coordinate relaxation
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Cites Work
- The eigenvalue problem \((A-\lambda B)x = 0\) for symmetric matrices of high order
- The iterative calculation of a few of the lowest eigenvalues and corresponding eigenvectors of large real-symmetric matrices
- Computational aspects of F. L. Bauer's simultaneous iteration method
- Modification of Nesbet's algorithm for the iterative evaluation of eigenvalues and eigenvectors of large matrices
- The iterative calculation of several of the lowest or highest eigenvalues and corresponding eigenvectors of very large symmetric matrices
- 𝑆𝑂𝑅-methods for the eigenvalue problem with large sparse matrices
