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Symmetric low‐rank corrections to quadratic models
Author(s) -
Qian Jiang,
Xu ShuFang,
Bai FengShan
Publication year - 2009
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.623
Subject(s) - rank (graph theory) , quadratic equation , mathematics , quadratic model , quadratic programming , mathematical optimization , algorithm , combinatorics , statistics , geometry , response surface methodology
In this paper, we study the quadratic model updating problems by using symmetric low‐rank correcting, which incorporates the measured model data into the analytical quadratic model to produce an adjusted model that matches the experimental model data, and minimizes the distance between the analytical and updated models. We give a necessary and sufficient condition on the existence of solutions to the symmetric low‐rank correcting problems under some mild conditions, and propose two algorithms for finding approximate solutions to the corresponding optimization problems. The good performance of the two algorithms is illustrated by numerical examples. Copyright © 2008 John Wiley & Sons, Ltd.