A practical procedure for identifying time-varying nonlinear systems using basis sequence approximations

We approximate a class of time-varying nonlinear models, called the time-varying Hammerstein series, using basis sequences in order to reduce the number of coefficients required in system modelling. The problem is motivated by the practical need to parsimoniously characterise time-varying nonlinear...

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Bibliographic Details
Main Authors: Ralston, J.C., Boashash, B., Zoubir, A.M.
Format: Conference Proceeding
Language:English
Subjects:
Australia
Equations
Kernel
Nonlinear systems
Parameter estimation
Signal processing
System identification
Time varying systems
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Description
Summary:We approximate a class of time-varying nonlinear models, called the time-varying Hammerstein series, using basis sequences in order to reduce the number of coefficients required in system modelling. The problem is motivated by the practical need to parsimoniously characterise time-varying nonlinear systems. A significant advantage of the approach is that only a single input-output record is required to obtain least-squares estimates of the model parameters. The judicious selection of basis sequence is also discussed. The method represents a simple and practical time-varying nonlinear system identification procedure. Examples are presented to demonstrate the usefulness of the technique.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.1996.550176