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Self-Organizing Maps

✍ Scribed by Professor Teuvo Kohonen (auth.)


Publisher
Springer Berlin Heidelberg
Year
1995
Tongue
English
Leaves
371
Series
Springer Series in Information Sciences 30
Category
Library

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✦ Synopsis


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.

✦ Table of Contents


Front Matter....Pages I-XV
Mathematical Preliminaries....Pages 1-50
Justification of Neural Modeling....Pages 51-75
The Basic SOM....Pages 77-130
Physiological Interpretation of SOM....Pages 131-141
Variants of SOM....Pages 143-173
Learning Vector Quantization....Pages 175-189
Applications....Pages 191-213
Hardware for SOM....Pages 215-230
An Overview of SOM Literature....Pages 231-252
Glossary of β€œNeural” Terms....Pages 253-281
Back Matter....Pages 283-364

✦ Subjects


Biophysics and Biological Physics;Communications Engineering, Networks;Mathematics, general


πŸ“œ SIMILAR VOLUMES


Self-Organizing Maps
✍ Professor Teuvo Kohonen (auth.) πŸ“‚ Library πŸ“… 1997 πŸ› Springer Berlin Heidelberg 🌐 English

<B>Self-Organizing Maps </B>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, fundam

Self-Organizing Maps
✍ Professor Teuvo Kohonen (auth.) πŸ“‚ Library πŸ“… 2001 πŸ› Springer-Verlag Berlin Heidelberg 🌐 English

<p>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

Self-Organizing Maps
✍ Teuvo Kohonen πŸ“‚ Library πŸ“… 1997 πŸ› Springer 🌐 English

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, experimenta