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An efficient method for computing eigenvalues of a real normal matrix

✍ Scribed by B.B Zhou; R.P Brent

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
221 KB
Volume
63
Category
Article
ISSN
0743-7315

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✦ Synopsis

Jacobi-based algorithms have attracted attention as they have a high degree of potential parallelism and may be more accurate than QR-based algorithms. In this paper we discuss how to design efficient Jacobi-like algorithms for eigenvalue decomposition of a real normal matrix. We introduce a block Jacobi-like method. This method uses only real arithmetic and orthogonal similarity transformations and achieves ultimate quadratic convergence. A theoretical analysis is conducted and some experimental results are presented.

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