Consistency of system identification by global total least squares
type: Item
instance of: scholarly article
title: Consistency of system identification by global total least squares
zbMATH Open document ID: 0934.93066
DOI: 10.1016/S0005-1098(99)00006-0
published in: Automatica
publication date: 1999-09-02T00:00:00Z
review text: The global total least squares (GTLS) approach to the identification of multiple-input multiple-output (MIMO) discrete-time linear systems within a stochastic framework is considered. The aim is to find models with minimal error for a given a priori bound on the model complexity. It is assumed that the observed time-series data come from a multivariable stationary stochastic process and statistical properties of the method are investigated. Sufficient conditions for the almost sure consistency of the GTLS estimate for the class of factor (suitably decomposed) models are established. Under these conditions the identified model converges, as the number of observations tends to infinity, to an optimal approximation of the data generating process. The theoretical results are illustrated by computer simulations.
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 93B30
Mathematics Subject Classification ID: 93E24
zbMATH DE Number: 1331906
zbMATH Keywords: stochastic system
zbMATH Keywords: global total least squares identification
zbMATH Keywords: discrete-time linear systems
zbMATH Keywords: a priori bound on the model complexity
zbMATH Keywords: almost sure consistency
author: Christiaan Heij
author: Wolfgang Scherrer
reviewed by: Zygmunt Hasiewicz
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 1331906