Self-organizing maps

Author(s)

• Kohonen, Teuvo

Bibliographic Information

Self-organizing maps

Teuvo Kohonen

（Springer series in information sciences, 30）（Physics and astronomy online library）

Springer, c2001

3rd ed

Note

Includes bibliographical references (p. [403]-486) and index

Description and Table of Contents

Description

The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. About 4000 research articles on it have appeared in the open literature, and many industrial projects use the SOM as a tool for solving hard real world problems. Many fields of science have adopted the SOM as a standard analytical tool: statistics, signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. This new edition includes a survey of over 2000 contemporary studies to cover the newest results. Case examples are provided with detailed formulae, illustrations, and tables. Further, a new chapter on software tools for SOM has been included whilst other chapters have been extended and reorganised.

Table of Contents

1. Mathematical Preliminaries.- 2. Neural Modeling.- 3. The Basic SOM.- 4. Physiological Interpretation of SOM.- 5. Variants of SOM.- 6. Learning Vector Quantization.- 7. Applications.- 8. Software Tools for SOM.- 9. Hardware for SOM.- 10. An Overview of SOM Literature.- 11. Glossary of "Neural" Terms.- References.

by "Nielsen BookData"

• NCID: BA49661849
• ISBN:
  • 9783540679219
• LCCN: 00052663
• Country Code: gw
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: Berlin ; New York
• Pages/Volumes: xx, 501 p.
• Size: 24 cm
• Classification:
  • LCC : QA76.87
  • DC21 : 006.3/2
• Subject Headings:
  • LCSH : Neural networks (Computer science)
  • LCSH : Self-organizing maps
• Parent Bibliography ID:
  • BA00122781
  • BA48464922