On-line Identification of Nonlinear Systems Using Volterra Polynomial Basis Function Neural Networks

On-line Identification of Nonlinear Systems Using Volterra Polynomial Basis Function Neural Networks
Author: Guo Ping Liu
Publisher:
Total Pages:
Release: 1996
Genre: Automatic control
ISBN:
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On-line Identification of Nonlinear Systems Using Volterra Polynomial Basis Function Neural Networks
Language: en
Pages:

On-line Identification of Nonlinear Systems Using Volterra Polynomial Basis Function Neural Networks

Authors: Guo Ping Liu
Categories: Automatic control
Type: BOOK - Published: 1996 - Publisher:

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Nonlinear Identification and Control
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Nonlinear Identification and Control

Authors: G.P. Liu
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

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The purpose of this monograph is to give the broad aspects of nonlinear identification and control using neural networks. It uses a number of simulated and indu
Nonlinear System Identification
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Nonlinear System Identification

Authors: Oliver Nelles
Categories: Technology & Engineering
Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media

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Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic syst
Nonlinear System Identification
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Nonlinear System Identification

Authors: Oliver Nelles
Categories: Science
Type: BOOK - Published: 2020-09-09 - Publisher: Springer Nature

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This book provides engineers and scientists in academia and industry with a thorough understanding of the underlying principles of nonlinear system identificati
Identification of Nonlinear Systems Using Neural Networks and Polynomial Models
Language: en
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Identification of Nonlinear Systems Using Neural Networks and Polynomial Models

Authors: Andrzej Janczak
Categories: Technology & Engineering
Type: BOOK - Published: 2004-11-18 - Publisher: Springer Science & Business Media

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This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known appro