Please use this identifier to cite or link to this item: https://doi.org/10.1137/060656346
Title: A dual optimization approach to inverse quadratic eigenvalue problems with partial eigenstructure
Authors: Bai, Z.-J.
Chu, D. 
Sun, D. 
Keywords: Inverse eigenvalue problem
Nonlinear optimization
Partial eigenstructure
Quadratic eigenvalue problem
Issue Date: 2007
Citation: Bai, Z.-J., Chu, D., Sun, D. (2007). A dual optimization approach to inverse quadratic eigenvalue problems with partial eigenstructure. SIAM Journal on Scientific Computing 29 (6) : 2531-2561. ScholarBank@NUS Repository. https://doi.org/10.1137/060656346
Abstract: The inverse quadratic eigenvalue problem (IQEP) arises in the field of structural dynamics. It aims to find three symmetric matrices, known as the mass, the damping, and the stiffness matrices, such that they are closest to the given analytical matrices and satisfy the measured data. The difficulty of this problem lies in the fact that in applications the mass matrix should be positive definite and the stiffness matrix positive semidefinite. Based on an equivalent dual optimization version of the IQEP, we present a quadratically convergent Newton-type method. Our numerical experiments confirm the high efficiency of the proposed method. © 2007 Society for Industrial and Applied Mathematics.
Source Title: SIAM Journal on Scientific Computing
URI: http://scholarbank.nus.edu.sg/handle/10635/102635
ISSN: 10648275
DOI: 10.1137/060656346
Appears in Collections:Staff Publications

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