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Self-Organizing Maps

  • Teuvo Kohonen

Part of the Springer Series in Information Sciences book series (SSINF, volume 30)

Table of contents

  1. Front Matter
    Pages I-XVII
  2. Teuvo Kohonen
    Pages 1-58
  3. Teuvo Kohonen
    Pages 59-83
  4. Teuvo Kohonen
    Pages 85-144
  5. Teuvo Kohonen
    Pages 145-155
  6. Teuvo Kohonen
    Pages 157-201
  7. Teuvo Kohonen
    Pages 203-217
  8. Teuvo Kohonen
    Pages 219-260
  9. Teuvo Kohonen
    Pages 261-276
  10. Teuvo Kohonen
    Pages 277-301
  11. Teuvo Kohonen
    Pages 303-331
  12. Back Matter
    Pages 333-428

About this book

Introduction

Self-Organizing Maps deals with the most popular artificial neural-network algorithm of the unsupervised-learning category, viz. the Self-Organizing Map (SOM). As this book is the main monograph on the subject, it discusses all the relevant aspects ranging from the history, motivation, fundamentals, theory, variants, advances, and applications, to the hardware of SOMs. An extensive literature survey of over 2000 contemporary studies is included. Thus, answers to the most frequently asked questions relating to this topic can be found in this volume. The subject is presented in a didactive manner and only a general theoretical background is required. The reader will be guided by the many case studies to the very frontier of modern research in this area.

Keywords

Adaptive and Learning Networks Adaptive und Lernende Netze Cluster Analysis Klassifikator Klusteranalyse Neural Network Pattern Recognition Self-Organ algorithms classification neural modeling neural networks self-organizing map

Authors and affiliations

  • Teuvo Kohonen
    • 1
  1. 1.Neural Networks Research CentreHelsinki University of TechnologyEspooFinland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-97966-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 1997
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-62017-4
  • Online ISBN 978-3-642-97966-8
  • Series Print ISSN 0720-678X
  • Buy this book on publisher's site