On the computation of the structured total least squares estimator
Markovsky, I., Van Huffel, S. and Kukush, A. (2004) On the computation of the structured total least squares estimator. Numerical Linear Algebra with Applications, 11, 591-608,.
A class of structured total least squares problems is considered, in which the extended data matrix is partitioned into blocks and each of the blocks is (block) Toeplitz/Hankel structured, unstructured, or noise free. We describe the implementation of two types of numerical solution methods for this problem: i) standard local optimization methods in combination with efficient evaluation of the cost function and its gradient, 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. Application of the structured total least squares problem for system identification and model reduction is described and illustrated with numerical examples.
|Keywords:||parameter estimation; total least squares; structured total least squares; system identification; Hankel low rank approximation; model reduction.|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||06 Jan 2007|
|Last Modified:||18 Aug 2012 04:06|
|Contributors:||Markovsky, I. (Author)
Van Huffel, S. (Author)
Kukush, A. (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||9|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)