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

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51 Citaten (Scopus)

Samenvatting

This paper studies the linear dynamic errors-in-variables problem in the frequency domain. First the identifiability is shown under relaxed conditions. Next 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. The ML estimates are calculated via a computational simple and numerical stable Newton-Gauss minimization scheme. Finally the Cramr-Rao lower bound is derived.
Originele taal-2English
Pagina's (van-tot)621-630
Aantal pagina's10
TijdschriftAutomatica
Volume43
Nummer van het tijdschriftAutomatica
StatusPublished - 1 feb 2007

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