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Taschenbuch. Condition: Neu. Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis | Marcin Mrugalski | Taschenbuch | xxi | Englisch | 2015 | Springer | EAN 9783319032863 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Published by Springer International Publishing, Springer International Publishing Aug 2013, 2013
ISBN 10: 331901546X ISBN 13: 9783319015460
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 204 pp. Englisch.
Published by Springer International Publishing, Springer International Publishing, 2015
ISBN 10: 3319032860 ISBN 13: 9783319032863
Language: English
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Published by Springer International Publishing, 2013
ISBN 10: 331901546X ISBN 13: 9783319015460
Language: English
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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Published by Springer International Publishing Aug 2013, 2013
ISBN 10: 331901546X ISBN 13: 9783319015460
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 204 pp. Englisch.
Published by Springer International Publishing Aug 2015, 2015
ISBN 10: 3319032860 ISBN 13: 9783319032863
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 208 pp. Englisch.
Published by Springer International Publishing, 2015
ISBN 10: 3319032860 ISBN 13: 9783319032863
Language: English
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemesDetails neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems.
Published by Springer International Publishing, 2013
ISBN 10: 331901546X ISBN 13: 9783319015460
Language: English
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemesDetails neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems.
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Published by Springer International Publishing, 2013
ISBN 10: 331901546X ISBN 13: 9783319015460
Language: English
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Buch. Condition: Neu. Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis | Marcin Mrugalski | Buch | xxi | Englisch | 2013 | Springer International Publishing | EAN 9783319015460 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Published by Springer International Publishing, Springer International Publishing Aug 2015, 2015
ISBN 10: 3319032860 ISBN 13: 9783319032863
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 208 pp. Englisch.
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand pp. 208.
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Condition: New. PRINT ON DEMAND pp. 208.