Frequency domain maximum likelihood estimation of linear dynamic errors-in-variables models

被引：43

作者：

Pintelon, R. ^{[1
]}

Schoukens, J. ^{[1
]}

机构：

[1] Vrije Univ Brussels, Dept ELEC, B-1050 Brussels, Belgium

来源：

AUTOMATICA | 2007年 / 43卷 / 04期

关键词：

errors-in-variables; maximum likelihood; continuous-time; discrete-time; frequency domain;

D O I：

10.1016/j.automatica.2006.10.004

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper studies the linear dynamic errors-in-variables problem for filtered white noise excitations. First, a frequency domain Gaussian maximum likelihood (ML) estimator is constructed that can handle discrete-time as well as continuous-time models on (a) part(s) of the unit circle or imaginary axis. Next, the ML estimates are calculated via a computationally simple and numerically stable Gauss-Newton minimization scheme. Finally, the Cramer-Rao lower bound is derived. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：621 / 630

页数：10

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