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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
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.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: ThriftBooks-Atlanta, AUSTELL, GA, USA
Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Artikel-Nr. G3540620176I4N00
Anzahl: 1 verfügbar
Anbieter: AwesomeBooks, Wallingford, Vereinigtes Königreich
Paperback. Zustand: Very Good. Self-Organizing Maps: Second edition (Springer Series in Information Sciences) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Artikel-Nr. 7719-9783540620174
Anzahl: 1 verfügbar
Anbieter: Bahamut Media, Reading, Vereinigtes Königreich
Paperback. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee. Artikel-Nr. 6545-9783540620174
Anzahl: 1 verfügbar
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
Zustand: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9783540620174. Artikel-Nr. 8959807
Anzahl: 1 verfügbar
Anbieter: Leopolis, Kraków, Polen
Soft cover. Zustand: Fine. 8vo (23.5 cm), XVII, 426 pp. Printed wrappers. A seminal work that unveils the groundbreaking concept of self-organizing maps (SOMs) and their profound impact on the field of artificial intelligence. In this influential book, Kohonen introduces an innovative neural network architecture that mimics the self-organizing principles of the human brain, enabling machines to efficiently analyze and classify complex data patterns. Kohonen's work revolutionizes the field of unsupervised learning by presenting a powerful algorithmic approach that enables machines to learn and adapt without explicit guidance. The self-organizing map algorithm constructs a low-dimensional representation of high-dimensional data, effectively capturing the inherent structure and relationships within the input space. By arranging data samples on a map-like grid, SOMs reveal hidden patterns, clusters, and topological relationships, facilitating data exploration and visualization. The book provides a comprehensive introduction to SOMs, offering a clear and accessible explanation of the underlying principles, mathematical foundations, and algorithmic implementation. Kohonen's intuitive and lucid writing style guides readers through the intricate details of SOMs, making the concepts approachable for both novices and experts in the field. Moreover, "Self-Organizing Maps" showcases the broad range of applications where SOMs have proven invaluable. From data mining and pattern recognition to image and speech processing, Kohonen demonstrates the versatility of SOMs in various domains. The book illustrates real-world case studies and practical examples, emphasizing the potential of SOMs as a powerful tool for solving complex problems across multiple disciplines. Artikel-Nr. 008332
Anzahl: 1 verfügbar