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-XV
  2. Teuvo Kohonen
    Pages 1-50
  3. Teuvo Kohonen
    Pages 51-75
  4. Teuvo Kohonen
    Pages 77-130
  5. Teuvo Kohonen
    Pages 131-141
  6. Teuvo Kohonen
    Pages 143-173
  7. Teuvo Kohonen
    Pages 175-189
  8. Teuvo Kohonen
    Pages 191-213
  9. Teuvo Kohonen
    Pages 215-230
  10. Teuvo Kohonen
    Pages 231-252
  11. Teuvo Kohonen
    Pages 253-281
  12. Back Matter
    Pages 283-364

About this book

Introduction

The Self-Organizing Map (SOM) algorithm was introduced by the author in 1981. Its theory and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technolgies have already been based on it. The most important practical applications are in exploratory data analysis, pattern recognition, speech analysis, robotics, industrial and medical diagnostics, instrumentation, and control, and literally hundreds of other tasks. In this monograph the mathematical preliminaries, background, basic ideas, and implications are expounded in a clear, well-organized form, accessible without prior expert knowledge. Still the contents are handled with theoretical rigor.

Keywords

Mathematica algorithms artificial neural network calculus classification data analysis filters nervous system neural modeling neural networks pattern recognition self-organizing map signal processing telecommunications unsupervised learning

Authors and affiliations

  • Teuvo Kohonen
    • 1
  1. 1.Laboratory of Computer and Information ScienceHelsinki University of TechnologyEspoo 15Finland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-97610-0
  • Copyright Information Springer-Verlag Berlin Heidelberg 1995
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-97612-4
  • Online ISBN 978-3-642-97610-0
  • Series Print ISSN 0720-678X
  • About this book