Premium
On the computation of the multivariate structured total least squares estimator
Author(s) -
Markovsky Ivan,
Huffel Sabine Van,
Kukush Alexander
Publication year - 2004
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.361
Subject(s) - mathematics , toeplitz matrix , estimator , computation , multivariate statistics , least squares function approximation , mathematical optimization , total least squares , algorithm , generalized least squares , statistics , singular value decomposition , pure mathematics
A multivariate structured total least squares problem is considered, in which the extended data matrix is partitioned into blocks and each of the blocks is Toeplitz/Hankel structured, unstructured, or noise free. Two types of numerical solution methods for this problem are proposed: (i) standard local optimization methods in combination with efficient evaluation of the cost function and its first derivative, and (ii) an iterative procedure proposed originally for the element‐wise weighted total least squares problem. The computational efficiency of the proposed methods is compared with this of alternative methods. Copyright © 2004 John Wiley & Sons, Ltd.