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Use of multilayer feedforward neural networks in identification and control of Wiener model

Date

1996

Authors

Chandrasekar, V., author
Karim, M. N., author
Al-Duwaish, H., author
IEE, publisher

Journal Title

Journal ISSN

Volume Title

Abstract

The problem of identification and control of a Wiener model is studied. The proposed identification model uses a hybrid model consisting of a linear autoregressive moving average model in cascade with a multilayer feed forward neural network. A two-step procedure is proposed to estimate the linear and nonlinear parts separately. Control of the Wiener model can be achieved by inserting the inverse of the static nonlinearity in the appropriate loop locations. Simulation results illustrate the performance of the proposed method.

Description

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Subject

nonlinear system identification
Wiener model
neural networks

Citation

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