Identification of a class of time-varying nonlinear systems using basis sequences

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Identification of a class of time-varying nonlinear systems using basis sequences

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dc.contributor.author Ralston, J.C
dc.contributor.author Zoubir, A.M
dc.contributor.author Boashash, B
dc.date.accessioned 2012-09-18T02:31:17Z
dc.date.available 2012-09-18T02:31:17Z
dc.date.issued 1996
dc.identifier.citation Proc. of Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on, 1996, pp. 161-164 en_US
dc.identifier.other Digital Object Identifier : 10.1109/TFSA.1996.546711
dc.identifier.uri http://hdl.handle.net/10576/10873
dc.description This paper shows that the time-varying Hammerstein seriescan be used for a wide range of time-varying nonlinear system identification problems. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
dc.description.abstract We consider the identification of a class of time-varying nonlinear systems, called the time-varying Hammerstein series. This identification problem is motivated by the practical need to characterise time-varying nonlinearsystems in a simple and parsimonious manner. Basis sequences are introduced to facilitate a reduction in systemparameterisation and also to make the estimation task tractable. A significant advantage of the approach is that only a single input-output record is required to obtain least-squares estimates of the model coefficients. The selection of basis sequences and basis order is also discussed. Simulated and real data results are presented to indicate the usefulness of the proposed identification technique. We were interested in applying the time-varyingnonlinear system identification procedure to a modelling scenario in seismology en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject basis order en_US
dc.subject basis sequences en_US
dc.subject identification en_US
dc.subject least-squares estimates en_US
dc.subject model coefficients en_US
dc.subject real data results en_US
dc.subject seismic signal modelling en_US
dc.subject seismology en_US
dc.subject simulated data results en_US
dc.subject single input-output record en_US
dc.subject system parameters en_US
dc.subject time-varying Hammerstein series en_US
dc.subject time-varying nonlinear systems en_US
dc.subject seismic signal modelling en_US
dc.subject Walsh bases en_US
dc.subject Slepian bases en_US
dc.title Identification of a class of time-varying nonlinear systems using basis sequences en_US
dc.type Article en_US

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