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Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

Marcin Mrugalski

134,32 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2015
Materia
Inteligencia artificial
ISBN:
9783319032863
134,32 €
IVA incluido
Disponible

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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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Otros libros del autor

  • Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis
    Marcin Mrugalski
    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...