On frequency-domain identification of linear systems

Author

Kollar, Istvan

Author_Institution

Dept. of Meas. & Instrum. Eng., Tech. Univ., Budapest, Hungary

Volume

42

Issue

1

fYear

1993

fDate

2/1/1993 12:00:00 AM

Firstpage

2

Lastpage

6

Abstract

The maximum-likelihood estimation of the parameters of linear systems and the properties of the estimator (Estimator for Linear Systems, ELiS) have been described by R. Pintelson and J. Schoukens (see ibid., vol. 39, no.4, p.565-573, Aug. 1990). The mathematics used in the development of the method and the proofs is rather involved, although several statements can be understood in heuristic terms. The present author discusses the complex-domain description of the method, which results in much simpler expressions. The method is compared to other formulations, giving more insight into the properties of the estimate. It turns out that robustness is at least partly due to the least-squares formulation. Derivations are avoided where possible, and intuitive explanations are given instead

Keywords

estimation theory; frequency-domain analysis; least squares approximations; linear systems; maximum likelihood estimation; parameter estimation; ELiS; complex-domain; cost function; covariance matrix; frequency-domain identification; least-squares formulation; linear systems; maximum-likelihood estimation; noise model; robustness; Cost function; Delay; Frequency; Gaussian noise; Instrumentation and measurement; Linear systems; Mathematics; Maximum likelihood estimation; Noise robustness; Transfer functions;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.206670

Filename

206670