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Neural Networks : A Systematic Introduction.

By: Contributor(s): Material type: TextTextPublisher: Berlin, Heidelberg : Springer Berlin / Heidelberg, 1996Copyright date: ©1996Edition: 1st edDescription: 1 online resource (511 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642610684
Subject(s): Genre/Form: Additional physical formats: Print version:: Neural NetworksLOC classification:
  • Q334-342
Online resources:
Contents:
Neural Networks -- Copyright -- Foreword -- Preface -- Table of Contents -- 1. The Biological Paradigm -- 2. Threshold Logic -- 3. Weighted Networks - The Perceptron -- 4. Perceptron Learning -- 5. Unsupervised Learning and Clustering Algorithms -- 6. One and Two Layered Networks -- 7. The Backpropagation Algorithm -- 8. Fast Learning Algorithms -- 9. Statistics and Neural Networks -- 10. The Complexity of Learning -- 11. Fuzzy Logic -- 12. Associative Networks -- 13. The Hopfield Model -- 14. Stochastic Networks -- 15. Kohonen Networks -- 16. Modular Neural Networks -- 17. Genetic Algorithms -- 18. Hardware for Neural Networks -- References -- Index.
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Neural Networks -- Copyright -- Foreword -- Preface -- Table of Contents -- 1. The Biological Paradigm -- 2. Threshold Logic -- 3. Weighted Networks - The Perceptron -- 4. Perceptron Learning -- 5. Unsupervised Learning and Clustering Algorithms -- 6. One and Two Layered Networks -- 7. The Backpropagation Algorithm -- 8. Fast Learning Algorithms -- 9. Statistics and Neural Networks -- 10. The Complexity of Learning -- 11. Fuzzy Logic -- 12. Associative Networks -- 13. The Hopfield Model -- 14. Stochastic Networks -- 15. Kohonen Networks -- 16. Modular Neural Networks -- 17. Genetic Algorithms -- 18. Hardware for Neural Networks -- References -- Index.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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