Neural Network Applications in Control

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The aim is to present an introduction to, and an overview of, the present state of neural network research and development, with an emphasis on control systems application studies. The book is useful to a range of levels of reader. The earlier chapters introduce the more popular networks and the fundamental control principles, these are followed by a series of application studies, most of which are industrially based, and the book concludes with a consideration of some recent research.
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Editorial Reviews

Eleven research specialists discuss aspects of neural networks, the foundation for computational forms of artificial intelligence. The essays introduce the basic principles, design features, and application studies in multi-layer perceptron back-propagation networks, Kohenen nets, n-tuple nets, and radial basis function networks. Specific essays examine topics in: neurocontrol, chemical process application, vision and speech applications, and neurofuzzy adaptive modelling. Includes illustrative graphs and computations. Annotation c. Book News, Inc., Portland, OR (
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Product Details

  • ISBN-13: 9780852968529
  • Publisher: Institution of Engineering and Technology (IET)
  • Publication date: 1/1/1995
  • Series: IEE Control Engineering Ser.
  • Pages: 309
  • Product dimensions: 6.40 (w) x 9.30 (h) x 0.90 (d)

Table of Contents

Part 1 Introduction: neural networks - an introduction, Kevin Warwick
digital neural networks, A. Redgers and Igor Aleksander
fundamentals of neurocontrol - a survey, R. Zbikowski and Peter Gawthrop
selection of neural network structures - some approximation theory guidelines, John Mason and Patrick Parks. Part 2 Applications: electric power and chemical process applications, George Irwin et al
studies in neural network based control, Ken Hunt and D. Sbarbaro
applications of dynamic neural networks in state estimation and process control, P. Turner et al
speech, vision and colour applications, R. Mitchell and J. Bishop
real-time drive control with neural networks, D. Neumerkel et al
fuzzy-neural control in intensive care blood pressure management, D. Linkens. Part 3 Recent advances: neural networks and system identification, Steve Billings and S. Chen
neurofuzzy adaptive modelling and construction of nonlinear dynamical processes, K. Bossley et al.
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