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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering
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Neural Network Systems Techniques and Applications, Volume 7 - Advances in Theory and Applications (Hardcover)
Loot Price: R2,160
Discovery Miles 21 600
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Neural Network Systems Techniques and Applications, Volume 7 - Advances in Theory and Applications (Hardcover)
Series: Control and Dynamic Systems
Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.
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The book emphasizes neural network structures for achieving
practical and effective systems, and provides many examples.
Practitioners, researchers, and students in industrial,
manufacturing, electrical, mechanical, and production engineering
will find this volume a unique and comprehensive reference source
for diverse application methodologies.
Control and Dynamic Systems covers the important topics of highly
effective Orthogonal Activation Function Based Neural Network
System Architecture, multi-layer recurrent neural networks for
synthesizing and implementing real-time linear control, adaptive
control of unknown nonlinear dynamical systems, Optimal Tracking
Neural Controller techniques, a consideration of unified
approximation theory and applications, techniques for the
determination of multi-variable nonlinear model structures for
dynamic systems with a detailed treatment of relevant system model
input determination, High Order Neural Networks and Recurrent High
Order Neural Networks, High Order Moment Neural Array Systems,
Online Learning Neural Network controllers, and Radial Bias
Function techniques.
Key Features
Coverage includes:
* Orthogonal Activation Function Based Neural Network System
Architecture (OAFNN)
* Multilayer recurrent neural networks for synthesizing and
implementing real-time linear control
* Adaptive control of unknown nonlinear dynamical systems
* Optimal Tracking Neural Controller techniques
* Consideration of unified approximation theory and
applications
* Techniques for determining multivariable nonlinear model
structures for dynamic systems,
with a detailed treatment of relevant system model input
determination
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