Teuvo Kohonen9783540679219, 3540679219
The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. Many fields of science have adopted the SOM as a standard analytical tool: in statistics,signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. A new area is organization of very large document collections. The SOM is also one of the most realistic models of the biological brain functions.This new edition includes a survey of over 2000 contemporary studies to cover the newest results; the case examples were provided with detailed formulae, illustrations and tables; a new chapter on software tools for SOM was written, other chapters were extended or reorganized. |
Table of contents :
Front Matter….Pages I-XVII
Mathematical Preliminaries….Pages 1-58
Justification of Neural Modeling….Pages 59-83
The Basic SOM….Pages 85-144
Physiological Interpretation of SOM….Pages 145-155
Variants of SOM….Pages 157-201
Learning Vector Quantization….Pages 203-217
Applications….Pages 219-260
Hardware for SOM….Pages 261-276
An Overview of SOM Literature….Pages 277-301
Glossary of “Neural” Terms….Pages 303-331
Back Matter….Pages 333-428 |
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