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Home > Computing and Information Technology > Computer science > Artificial intelligence > Neural networks and fuzzy systems > Self-Organizing Maps: (30 Springer Series in Information Sciences)
Self-Organizing Maps: (30 Springer Series in Information Sciences)

Self-Organizing Maps: (30 Springer Series in Information Sciences)


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About the Book

This is a study of the most popular artificial neural network algorithm in the unsupervized-learning category - the self-organizing map (SOM). This monograph discusses all the relevant aspects ranging from the history, motivation, fundamentals, theory, variants, advances, and applications, to the hardware of the SOMs. An extensive literature survey of over 2000 contemporary studies is also included. Thus, answers to the most frequently asked questions relating to this topic should be found in this volume.

Table of Contents:
From the contents: Mathematical Preliminaries.- Justification of Neural Modeling.- The Basic SOM.- Pysiological Interpretation of SOM.- Variants of SOM.- Learning Vector Quantization.- Applications.- Hardware for SOM.- An Overview of SOM Literature.- Glossary of 'Neural' Terms.- References.

Review :
"Rarely do books come along with an information density and value of content far above average. We now have another book in this category...a marvelous tool for finding just about any information that exists regarding self-organising maps. Rarely has any subject been provided with such an index of knowledge...Kohonen has created a masterpiece. I unhesitatingly recommend it." IEEE


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Product Details
  • ISBN-13: 9783540620174
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Publisher Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Edition: Revised edition
  • Language: English
  • Series Title: 30 Springer Series in Information Sciences
  • Width: 155 mm
  • ISBN-10: 3540620176
  • Publisher Date: 17 Apr 1997
  • Binding: Paperback
  • Height: 235 mm
  • Returnable: N
  • Weight: 680 gr


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