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Artificial Neural Networks

An Introduction to ANN Theory and Practice

  • Book
  • © 1995

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Editors:
  1. P. J. Braspenning
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  2. F. Thuijsman
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  3. A. J. M. M. Weijters
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 931)

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Table of contents (15 chapters)

  1. Front Matter

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  2. Introduction: Neural networks as associative devices

    • P. J. Braspenning
    Pages 1-9

  3. Backpropagation networks for Grapheme-Phoneme conversion: A non-technical introduction

    • A. J. M. M. Weijters, G. A. J. Hoppenbrouwers
    Pages 11-36

  4. Back Propagation

    • J. Henseler
    Pages 37-66

  5. Perceptrons

    • H. J. M. Peters
    Pages 67-81

  6. Kohonen network

    • O. J. Vrieze
    Pages 83-100

  7. Adaptive Resonance Theory

    • E. O. Postma, P. T. W. Hudson
    Pages 101-117

  8. Boltzmann Machines

    • F. C. R. Spieksma
    Pages 119-129

  9. Representation issues in Boltzmann machines

    • J. H. J. Lenting
    Pages 131-144

  10. Optimisation networks

    • E. O. Postma
    Pages 145-156

  11. Local search in combinatorial optimization

    • Y. Crama, A. W. J. Kolen, E. J. Pesch
    Pages 157-174

  12. Process identification and control

    • P. Boekhoudt
    Pages 175-204

  13. Learning controllers using neural networks

    • W. T. C. van Luenen
    Pages 205-233

  14. Key issues for successful industrial neural-network applications: An application in geology

    • H. R. A. Cardon, R. van Hoogstraten
    Pages 235-245

  15. Neural cognodynamics

    • P. J. Braspenning
    Pages 247-271

  16. Choosing and using a neural net

    • P. T. W. Hudson, E. O. Postma
    Pages 273-287

  17. Back Matter

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Keywords

About this book

This book presents carefully revised versions of tutorial lectures given during a School on Artificial Neural Networks for the industrial world held at the University of Limburg in Maastricht, Belgium.
The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM.

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