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Introduction to Neural Networks

  • Textbook
  • © 1994

Overview

Authors:
  1. Phil Picton

    1. Faculty of Technology, The Open University, UK

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-viii
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  2. What is a Neural Network?

    • Phil Picton
    Pages 1-12

  3. ADALINE

    • Phil Picton
    Pages 13-24

  4. Perceptrons

    • Phil Picton
    Pages 25-45

  5. Boolean Neural Networks

    • Phil Picton
    Pages 46-60

  6. Associative Memory and Feedback Networks

    • Phil Picton
    Pages 61-82

  7. Probabilistic Networks

    • Phil Picton
    Pages 83-94

  8. Self-Organizing Networks

    • Phil Picton
    Pages 95-115

  9. Neural Networks in Control Engineering

    • Phil Picton
    Pages 116-132

  10. Threshold Logic

    • Phil Picton
    Pages 133-142

  11. Implementation

    • Phil Picton
    Pages 143-157

  12. Conclusions

    • Phil Picton
    Pages 158-159

  13. Back Matter

    Pages 160-168
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Keywords

About this book

This book introduces neural networks. It describes what they are, what they can do and how they do it. While some scientific background is assumed, the reader is not expected to have any prior knowledge of neural networks. These networks are explained and discussed by means of examples, so that by the end of the book the reader will have a good overall knowledge of developments right up to current work in the field.

Authors and Affiliations

  • Faculty of Technology, The Open University, UK

    Phil Picton

Bibliographic Information

  • Book Title: Introduction to Neural Networks

  • Authors: Phil Picton

  • DOI: https://doi.org/10.1007/978-1-349-13530-1

  • Publisher: Red Globe Press London

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: P. D. Picton 1994

  • Edition Number: 1

  • Number of Pages: VIII, 168

  • Additional Information: Previously published under the imprint Palgrave

  • Topics: Artificial Intelligence

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