Asymptotic Uncertainty of Transfer Function Estimates Using Non-Parametric Noise Models

Rik Pintelon, M. Hong

Onderzoeksoutput: Conference paper

1 Citaat (Scopus)


Identification of parametric transfer function models from noisy input/output observations is an important task in many engineering applications. Besides the parametric model, the estimation algorithm used should also provide accurate confidence bounds. In addition it is important to know whether the proposed estimation algorithm has the lowest possible uncertainty within the class of consistent estimators. This paper handles these issues for the frequency domain Gaussian maximum likelihood estimator of rational transfer function models.
Originele taal-2English
TitelIMTC/2007, Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Warsaw, Poland, May 1-3, 2007
StatusPublished - 1 mei 2007
EvenementUnknown - Stockholm, Sweden
Duur: 21 sep 200925 sep 2009




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