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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 contr

Control theory. --- Neural networks (Computer science) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Dynamics --- Machine theory

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Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of data into orderly and informative patterns but they cannot solve every problem and consequently their application must be chosen carefully and appropriately.This book outlines how best to make use of neural networks. It enables newcomers to the technology to construct robust and meaningful non-linear models and classifiers and benefits th

Neural computers. --- Neural networks (Computer science) Neural computers. --- Neural networks (Computer science) --- Neural computers --- Engineering & Applied Sciences --- Computer Science --- Neural net computers --- Neural network computers --- Neurocomputers --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Electronic digital computers --- Natural computation --- Artificial intelligence --- Soft computing --- Neural Networks (Computer)

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Computer simulation. --- Neural networks (Computer science). --- Computer simulation --- Neural networks (Computer science) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing --- GENESIS (Computer file) --- General neural simulation system

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Neural networks (Computer science) --- Neural networks (Neurobiology) --- Nerve Net --- Neural Networks, Computer. --- Computational Neural Networks --- Connectionist Models --- Models, Neural Network --- Neural Network Models --- Neural Networks (Computer) --- Perceptrons --- Computational Neural Network --- Computer Neural Network --- Computer Neural Networks --- Connectionist Model --- Model, Connectionist --- Model, Neural Network --- Models, Connectionist --- Network Model, Neural --- Network Models, Neural --- Network, Computational Neural --- Network, Computer Neural --- Network, Neural (Computer) --- Networks, Computational Neural --- Networks, Computer Neural --- Networks, Neural (Computer) --- Neural Network (Computer) --- Neural Network Model --- Neural Network, Computational --- Neural Network, Computer --- Neural Networks, Computational --- Perceptron --- Neural Networks (Anatomic) --- Nerve Nets --- Net, Nerve --- Nets, Nerve --- Network, Neural (Anatomic) --- Networks, Neural (Anatomic) --- Neural Network (Anatomic) --- Biological neural networks --- Nets, Neural (Neurobiology) --- Networks, Neural (Neurobiology) --- Neural nets (Neurobiology) --- Cognitive neuroscience --- Neurobiology --- Neural circuitry --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Nerve Net.

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Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text devotes broad coverage toa unified view of optimal learning, orthogonal transformation techniques, sequential constructive techniques, fast back propagation algorithms, techniques for neural networks with nonstationary or dynamic outputs, applications to constraint satisfaction,optimization issues and techniques for unsupervised learning neural networks, optimum Cerebellar Model of Articulation Controller

Computer science. --- Mathematical optimization. --- Neural networks (Computer science). --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Operations Research --- Neural networks (Computer science) --- Réseaux neuronaux (informatique) --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Artificial intelligence --- Natural computation --- Soft computing --- Mathematical optimization --- E-books