Electronic Resource

Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

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Penilaian

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The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems.

A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered.

All the concepts described in this book are illustrated by both simple academic illustrative examples and practical applications.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
1408000570	EB0002656	006.32 Mru a	Central Library (OPAC)	Available

Detail Information

Series Title

Studies in Computational Intelligence

Call Number

006.32 Mru a

Publisher

Switzerland : Springer Cham., 2013

Collation

xxi, 182p.: Ill.

Language

English

ISBN/ISSN

978-3-319-01547-7

Classification

006.32

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Neural Networks (Computer Science)

Specific Detail Info

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Statement of Responsibility

RTS

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