Jacobi-like algorithms for eigenvalue decomposition
163. B. B. Zhou and R. P. Brent,
Jacobi-like algorithms for eigenvalue decomposition of a real normal matrix
using real arithmetic,
Proceedings of the Tenth International Parallel Processing Symposium,
IEEE CS Press, 1996, 593-600.
Revised and extended version:
A block Jacobi-like method for eigenvalue decomposition of a real
normal matrix using real arithmetic, unpublished, 1998, 17 pp.
Paper:
pdf (122K),
ps (48K).
Revised and extended version:
dvi (28K),
pdf (175K),
ps (84K).
Abstract
In this paper we introduce a method for designing efficient Jacobi-like
algorithms for eigenvalue decomposition of a real normal matrix.
The algorithms use only real arithmetic and achieve ultimate quadratic
convergence. A theoretical analysis is conducted and some experimental
results are presented.
Comments
A preliminary version appeared as [159].
For a more recent paper on the same topic,
see [207].
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