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Identification of non-linear systems using general state-dependent models

Published online by Cambridge University Press:  14 July 2016

M. B. Priestley and
S. M. Heravi
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Abstract

This paper describes an extension of the SDM scheme introduced by Priestley (1980) to the problem of the identification of non-linear systems using only input/output records. It is shown that, under quite general assumptions on the structure of the system, it is possible to identify a non-linear relationship between the input and output processes via a modified version of the Kalman-type algorithm previously applied to the study of non-linear time series models. The paper includes a numerical study of data generated from various types of non-linear systems.

Keywords

NON-LINEAR MODELSKALMAN FILTERINGNON-PARAMETRIC FUNCTION FITTING

Information

Type
Part 4—Non-linear and Non-stationary Systems in Time Series
Information
Journal of Applied Probability , Volume 23 , Issue A: Essays in Time Series and Allied Processes , 1986, pp. 257 - 272
Copyright
Copyright © 1986 Applied Probability Trust 

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