Applications of neural networks in high assurance systems

"Applications of Neural Networks in High Assurance Systems" is the first book directly addressing a key part of neural network technology: methods used to pass the tough verification and validation (V&V) standards required in many safety-critical applications. The book presents what ki...

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Bibliografische gegevens
Andere auteurs: Schumann, Johann M., 1960- (Publishing director), Liu, Yan, 19..-...., chercheur en automatique et informatique (Publishing director)
Formaat: Livre numérique
Taal:Anglais
Gepubliceerd in: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Editie:1st ed. 2010.
Reeks:Studies in Computational Intelligence 268
Online toegang:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Opmerking: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Applications of Neural Networks in High Assurance Systems, Texte imprimé, 9783642106897
• Applications of Neural Networks in High Assurance Systems, Texte imprimé, 9783642106910
• Applications of Neural Networks in High Assurance Systems, Texte imprimé, 9783642106897
• Applications of Neural Networks in High Assurance Systems, Texte imprimé, 9783642262692
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245 0 0 |a Applications of neural networks in high assurance systems   |c edited by Johann Schumann, Yan Liu. 
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505 1 |a Application of Neural Networks in High Assurance Systems: A Survey Robust Adaptive Control Revisited: Semi-global Boundedness and Margins Network Complexity Analysis of Multilayer Feedforward Artificial Neural Networks Design and Flight Test of an Intelligent Flight Control System Stability, Convergence, and Verification and Validation Challenges of Neural Net Adaptive Flight Control Dynamic Allocation in Neural Networks for Adaptive Controllers Immune Systems Inspired Approach to Anomaly Detection, Fault Localization and Diagnosis in Automotive Engines Pitch-Depth Control of Submarine Operating in Shallow Water via Neuro-adaptive Approach Stick-Slip Friction Compensation Using a General Purpose Neuro-Adaptive Controller with Guaranteed Stability Modeling of Crude Oil Blending via Discrete-Time Neural Networks Adaptive Self-Tuning Wavelet Neural Network Controller for a Proton Exchange Membrane Fuel Cell Erratum to: Network Complexity Analysis of Multilayer Feedforward Artificial Neural Networks 
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520 |a "Applications of Neural Networks in High Assurance Systems" is the first book directly addressing a key part of neural network technology: methods used to pass the tough verification and validation (V&V) standards required in many safety-critical applications. The book presents what kinds of evaluation methods have been developed across many sectors, and how to pass the tests. A new adaptive structure of V&V is developed in this book, different from the simple six sigma methods usually used for large-scale systems and different from the theorem-based approach used for simplified component subsystems 
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