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عنوان
Artificial Neural Networks for Modelling and Control of Non-Linear Systems

پدید آورنده
by Johan A. K. Suykens, Joos P. L. Vandewalle, Bart L. R. Moor.

موضوع
Computer engineering.,Engineering.,Systems engineering.,Systems theory.

رده

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
9781441951588
(Number (ISBN
9781475724936

NATIONAL BIBLIOGRAPHY NUMBER

Number
dltt

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Artificial Neural Networks for Modelling and Control of Non-Linear Systems
General Material Designation
[Book]
First Statement of Responsibility
by Johan A. K. Suykens, Joos P. L. Vandewalle, Bart L. R. Moor.

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
Boston, MA :
Name of Publisher, Distributor, etc.
Imprint: Springer,
Date of Publication, Distribution, etc.
1996.

SUMMARY OR ABSTRACT

Text of Note
Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq Theory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9781441951588

PIECE

Title
Springer eBooks

TOPICAL NAME USED AS SUBJECT

Computer engineering.
Engineering.
Systems engineering.
Systems theory.

PERSONAL NAME - PRIMARY RESPONSIBILITY

Suykens, Johan A. K.

PERSONAL NAME - ALTERNATIVE RESPONSIBILITY

Moor, Bart L. R.
Vandewalle, Joos P. L.

CORPORATE BODY NAME - ALTERNATIVE RESPONSIBILITY

SpringerLink (Online service)

ORIGINATING SOURCE

Date of Transaction
20190301074200.0

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

Y

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