DocumentCode :
2909307
Title :
Application of Blind Identification to Nonlinear Calibration
Author :
Vanbeylen, Laurent ; Pintelon, Rik ; Schoukens, Johan
Author_Institution :
Vrije Univ. Brussel, Brussels
fYear :
2007
fDate :
1-3 May 2007
Firstpage :
1
Lastpage :
6
Abstract :
This paper handles the identification of nonlinear discrete-time Wiener systems from output measurements only (blind identification). Assuming that the unobserved input is white Gaussian noise, that the static nonlinearity is invertible, and that the output is observed without errors, a Gaussian maximum likelihood estimator is constructed. A two-step procedure for generating high quality starting values is presented as well. Finally, the proposed scheme is applied to both a simulation example and a laboratory experiment, illustrating the potential usefulness of the method for nonlinear calibration applications.
Keywords :
Gaussian noise; calibration; discrete time systems; identification; maximum likelihood estimation; nonlinear systems; stochastic processes; white noise; Gaussian maximum likelihood estimator; blind identification; nonlinear calibration; nonlinear discrete-time Wiener system; white Gaussian noise; Biological system modeling; Calibration; Distortion measurement; Gaussian noise; Maximum likelihood estimation; Noise robustness; Nonlinear dynamical systems; Nonlinear systems; Phase noise; Temperature sensors; Maximum likelihood; Wiener; blind identification; identification; nonlinearities; parameter estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference Proceedings, 2007. IMTC 2007. IEEE
Conference_Location :
Warsaw
ISSN :
1091-5281
Print_ISBN :
1-4244-0588-2
Type :
conf
DOI :
10.1109/IMTC.2007.379027
Filename :
4258128
Link To Document :
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