Self-Organizing Maps

Beschreibung

Self-Organizing Maps 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, fundamentals, theory, variants, advances, and applications, to the hardware of SOMs. An extensive literature survey of over 2000 contemporary studies is included. Thus, answers to the most frequently asked questions relating to this topic can be found in this volume. The subject is presented in a didactive manner and only a general theoretical background is required. The reader will be guided by the many case studies to the very frontier of modern research in this area.
The second, revised edition of this book was suggested by the impressive sales of the first edition. Fortunately this enabled us to incorporate new important results that had just been obtained. The ASSOM (Adaptive-Subspace SOM) is a new architecture in which invariant-feature detectors emerge in an unsupervised learning process. Its basic principle was already introduced in the first edition, but the motiva tion and theoretical discussion in the second edition is more thorough and consequent. New material has been added to Sect. 5.9 and this section has been rewritten totally. Correspondingly, Sect. 1.4, which deals with adaptive subspace classifiers in general and constitutes the prerequisite for the ASSOM principle, has also been extended and rewritten totally. Another new SOM development is the WEBSOM, a two-layer architecture intended for the organization of very large collections of full-text documents such as those found in the Internet and World Wide Web. This architecture was published after the first edition came out. The idea and results seemed to be so important that the new Sect. 7.8 has now been added to the second edition. Another addition that contains new results is Sect. 3.15, which describes the acceleration in the computing of very large SOMs. It was also felt that Chap. 7, which deals with 80M applications, had to be extended.
This book deals with the most popular artificial neural network algorithm in the unsupervised-leaning category, viz. the self-organizing map (SOM). As this book is the main monograph on the subject, it discusses all the relevant aspects. An extensive literature survey of over 2000 studies is included.

Autor*in

Teuvo Kohonen

Themen in »Self-Organizing Maps«

Adaptive and Learning Networks Adaptive und Lernende Netze Cluster Analysis Klassifikator Klusteranalyse Neural Network Pattern Recognition Self-Organ algorithms classification neural modeling neural networks self-organizing map

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"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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