Accuracy analysis of bias-eliminating least squares estimates for errors-in-variables systems

被引：25

作者：

Hong, Mei

Soederstroem, Torsten

Zheng, Wei Xing

机构：

[1] Uppsala Univ, Dept Informat Technol, Div Syst & Control, SE-75105 Uppsala, Sweden

[2] Univ Western Sydney, Sch Comp & Math, Penrith, NSW 1797, Australia

来源：

AUTOMATICA | 2007年 / 43卷 / 09期

基金：

澳大利亚研究理事会;

关键词：

system identification; parameter estimation; errors-in-variables; bias-eliminating least squares; accuracy;

D O I：

10.1016/j.automatica.2007.02.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The bias-eliminating least squares (BELS) method is one of the consistent estimators for identifying dynamic errors-in-variables systems. In this paper, we investigate the accuracy properties of the BELS estimates. An explicit expression for the normalized asymptotic covariance matrix of the estimated parameters is derived and supported by some numerical examples. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：1590 / 1596

页数：7

共 14 条

[1] IDENTIFICATION OF LINEAR-SYSTEMS WITH INPUT AND OUTPUT NOISE - THE KOOPMANS-LEVIN METHOD [J].