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A numerical method for solving inverse eigenvalue problems

Published online by Cambridge University Press:  15 August 2002

Hua Dai
Hua Dai*
Affiliation:
Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. The research was supported in part by the National Natural Science Foundation of China and the Jiangsu Province Natural Science Foundation. This work was done while the author was visiting CERFACS, France (March-August 1998).
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Abstract

Based on QR-like decomposition with column pivoting, a new and efficient numerical method for solving symmetric matrix inverse eigenvalue problems is proposed, which is suitable for both the distinct and multiple eigenvalue cases. A locally quadratic convergence analysis is given. Some numerical experiments are presented to illustrate our results.

Keywords

Inverse eigenvalue problemsQR-like decompositionleast squaresGauss-Newton method.
Type
Research Article
Information
ESAIM: Mathematical Modelling and Numerical Analysis , Volume 33 , Issue 5 , September 1999 , pp. 1003 - 1017
Copyright
© EDP Sciences, SMAI, 1999

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