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The formulation and numerical method for partial quadratic eigenvalue assignment problems
Author(s) -
Cai YunFeng,
Qian Jiang,
Xu ShuFang
Publication year - 2011
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/nla.745
Subject(s) - mathematics , eigenvalues and eigenvectors , norm (philosophy) , quadratic equation , divide and conquer eigenvalue algorithm , linear system , mathematical optimization , mathematical analysis , physics , geometry , quantum mechanics , political science , law
In this paper, we consider the minimum norm and robust partial quadratic eigenvalue assignment problems (PQEVAP). A complete theory on the existence of solutions for the PQEVAP is established. It is shown that solving the PQEVAP is essentially solving an eigenvalue assignment for a linear system of a much lower order, and the minimum norm and robust PQEVAPs are then concerning the minimum norm and robust eigenvalue assignment problems associated with this linear system. Based on this theory, an algorithm for solving the minimum norm and robust PQEVAPs is proposed, and its efficient behaviors are illustrated by some numerical examples. Copyright © 2010 John Wiley & Sons, Ltd.