The University of Southampton
University of Southampton Institutional Repository

Indirect Adaptive Neurofuzzy Estimation of Nonlinear Time Series

Wu, Z.Q. and Harris, C.J. (1996) Indirect Adaptive Neurofuzzy Estimation of Nonlinear Time Series Neural Network World, 6, (3), 407--416.

Record type: Article


Some classes of nonlinear systems or time series can be represented by an operating point dependent ARMA model. In this paper a neurofuzzy network structure is configured to identify such a model and the neural network is trained by the normalized back-propagation algorithm. The identified model is then converted to its equivalent state-space representation. Using this state-space form, a Kalman filter can be applied to estimate the state indirectly. A simulated example is given.

Full text not available from this repository.

More information

Published date: 1996
Additional Information: Special Issue for Neurofuzzy'96, April, Prague
Organisations: Southampton Wireless Group


Local EPrints ID: 250115
PURE UUID: 92220e1a-f46a-453d-95b2-0db440b1dd74

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:44

Export record


Author: Z.Q. Wu
Author: C.J. Harris

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.