Title :
A practical procedure for identifying time-varying nonlinear systems using basis sequence approximations
Author :
Ralston, Jonathon C. ; Boashash, Boualem ; Zoubir, Abdelhak M.
Author_Institution :
Signal Process. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
Abstract :
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
Keywords :
estimation theory; least squares approximations; nonlinear systems; parameter estimation; series (mathematics); signal processing; time-varying systems; basis sequence approximations; input signals; input-output record; least-squares estimates; model parameters; output signals; parameter estimation; system modelling; time-varying Hammerstein series; time-varying nonlinear system identification; Australia; Equations; Kernel; Nonlinear systems; Parameter estimation; Signal processing; System identification; Time varying systems;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3192-3
DOI :
10.1109/ICASSP.1996.550176