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A Real Time Neurofuzzy Modelling and State Estimation Scheme

A Real Time Neurofuzzy Modelling and State Estimation Scheme
A Real Time Neurofuzzy Modelling and State Estimation Scheme
The authors of this paper analyse the input-output relation of the fuzzy system with a functional rule base and B-spline basis functions as membership functions, constructing a kind of neurofuzzy network for system modelling with a simple but effective training algorithm. This model is applied to state estimation, a simulated example is given.
468-4732
Wu, Z.Q.
fc163085-376c-4f78-9e5a-77c8bc5038ad
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Morabito, F.C.
7388f404-d051-4d42-b090-22c2184f7422
Wu, Z.Q.
fc163085-376c-4f78-9e5a-77c8bc5038ad
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Morabito, F.C.
7388f404-d051-4d42-b090-22c2184f7422

Wu, Z.Q. and Harris, C.J. (1997) A Real Time Neurofuzzy Modelling and State Estimation Scheme. Morabito, F.C. (ed.) Advances in Intelligent Systems. pp. 468-4732 .

Record type: Conference or Workshop Item (Other)

Abstract

The authors of this paper analyse the input-output relation of the fuzzy system with a functional rule base and B-spline basis functions as membership functions, constructing a kind of neurofuzzy network for system modelling with a simple but effective training algorithm. This model is applied to state estimation, a simulated example is given.

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More information

Published date: 1997
Venue - Dates: Advances in Intelligent Systems, 1997-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250001
URI: http://eprints.soton.ac.uk/id/eprint/250001
PURE UUID: a4d989ee-85f3-4b39-82a8-d4b1ea7ca06c

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Date deposited: 03 May 2000
Last modified: 10 Dec 2021 20:06

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Contributors

Author: Z.Q. Wu
Author: C.J. Harris
Editor: F.C. Morabito

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