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Self-organizing maps (SOM) have proven to be of significant
economic value in the areas of finance, economic and marketing
applications. As a result, this area is rapidly becoming a
non-academic technology. This book looks at near state-of-the-art
SOM applications in the above areas, and is a multi-authored
volume, edited by Guido Deboeck, a leading exponent in the use of
computational methods in financial and economic forecasting, and by
the originator of SOM, Teuvo Kohonen. The book contains chapters on
applications of unsupervised neural networks using Kohonen's
self-organizing map approach.
Edited by Guido Deboeck, a leading exponent in the use of
computation intelligence methods in finance and economic
forecasting, and the originator of SOM, Teuvo Kohonen. An 8-page
color section makes this book unique, colorful and exciting to
read. Each chapter contains exercises and solutions, perfectly
suited to aid self-study.
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.
While the present edition is bibliographically the third one of
Vol. 8 of the Springer Series in Information Sciences (IS 8), the
book actually stems from Vol. 17 of the series Communication and
Cybernetics (CC 17), entitled Associative Memory - A
System-Theoretical Approach, which appeared in 1977. That book was
the first monograph on distributed associative memories, or
"content-addressable memories" as they are frequently called,
especially in neural-networks research. This author, however, would
like to reserve the term "content-addressable memory" for certain
more traditional constructs, the memory locations of which are
selected by parallel search. Such devices are discussed in Vol. 1
of the Springer Series in Information Sciences, Content-Addressable
Memories. This third edition of IS 8 is rather similar to the
second one. Two new discussions have been added: one to the end of
Chap. 5, and the other (the L VQ 2 algorithm) to the end of Chap.
7. Moreover, the convergence proof in Sect. 5.7.2 has been revised.
Due to continual progress in the large-scale integration of
semiconductor circuits, parallel computing principles can already
be met in low-cost sys tems: numerous examples exist in image
processing, for which special hard ware is implementable with quite
modest resources even by nonprofessional designers. Principles of
content addressing, if thoroughly understood, can thereby be
applied effectively using standard components. On the other hand,
mass storage based on associative principles still exists only in
the long term plans of computer technologists. This situation is
somewhat confused by the fact that certain expectations are held
for the development of new storage media such as optical memories
and "spin glasses" (metal alloys with low-density magnetic
impurities). Their technologies, however, may not ripen until after
"fifth generation" computers have been built. It seems that
software methods for content addressing, especially those based on
hash coding principles, are still holding their position firmly,
and a few innovations have been developed recently. As they need no
special hardware, one might expect that they will spread to a wide
circle of users. This monograph is based on an extensive literature
survey, most of which was published in the First Edition. I have
added Chap. ?, which contains a review of more recent work. This
updated book now has references to over 1200 original publications.
In the editing of the new material, I received valuable help from
Anneli HeimbUrger, M. Sc., and Mrs. Leila Koivisto."
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