Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

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The present book is devoted to problems of adaptation ofartificial neural networks to robust fault diagnosis schemes. Itpresents neural networks-based modelling and estimation techniques usedfor designing robust fault diagnosis schemes for non-linear dynamic systems.A part of the book focuses on fundamental issues such as architectures ofdynamic neural networks, methods for designing of neural networks and faultdiagnosis schemes as well as the importance of robustness. The book is of a tutorialvalue and can be perceived as a good starting point for the new-comersto this field. The book is also devoted to advanced schemes of description ofneural model uncertainty. In particular, the methods of computation of neuralnetworks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDHneural network is delivered. All the concepts described in this book are illustrated by both simpleacademic illustrative examples and practical applications.

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