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Download Self-Organizing Neural Networks: Recent Advances and Applications (Studies in Fuzziness and Soft Computing) fb2

by Udo Seiffert

  • ISBN: 3790814172
  • Category: Technology
  • Author: Udo Seiffert
  • Subcategory: Computer Science
  • Other formats: lrf lit lrf docx
  • Language: English
  • Publisher: Physica; 1 edition (December 18, 2001)
  • Pages: 278 pages
  • FB2 size: 1249 kb
  • EPUB size: 1215 kb
  • Rating: 4.5
  • Votes: 353
Download Self-Organizing Neural Networks: Recent Advances and Applications (Studies in Fuzziness and Soft Computing) fb2

Studies in Fuzziness and Soft Computing. Recent Advances and Applications. The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks

Studies in Fuzziness and Soft Computing. One of the most comprehensive books on SOMs. The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. A number of extensions and modifications have been developed during the last two decades.

The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial . Series: Studies in Fuzziness and Soft Computing (Book 78). Paperback: 278 pages. Publisher: Physica; Softcover reprint of the original 1st ed.

The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s.

Nevertheless, a rigorous definition of a measure for the state of organization of a SOM that is also natural, captures the intuitive properties of organization and proves to be useful in practice, is quite difficult to formulate. The goal of this chapter is to give an overview over the relevant problems in and different approaches towards the development of organization measures for SOMs.

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Recent advances in artificial neural networks. The catalog of self-organizing feature maps together with the index table is used as a compressed representation of the original data

Recent advances in artificial neural networks. Design and Applications. The main purpose of this book is to report recent advances in neural network paradigms and their applications. It is impossible to include all recent advances in this book; hence, only a sample has been included. This book consists of 10 chapters. The catalog of self-organizing feature maps together with the index table is used as a compressed representation of the original data. This technique is demonstrated on land-cover classification of multi-spectral satellite image showing increased speed.

SOM at its bestBy Thomas KleinThis book seems to be the most recent and comprehensive survey of SOM applications which are described in detail. Really good technical chapters, could have another one or two.

The scientific journal Categories and General Algebraic Structures with Applications is included in the Scopus database. Publisher of the journal is SHAHID BEHESHTI UNIV, FAC MATHEMATICAL SCIENCES, EVIN, TEHRAN, IRAN, 19839. Publisher country is Iran. View detail 5 minute of reading. Studies in Fuzziness and Soft Computing 1434-9922.

Book DescriptionIn recent years probabilistic graphical models, especially Bayesian networks and decision graphs .

Book DescriptionIn recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. In addition, Advances in Bayesian Networks presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval.

The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative community of interna­ tional researchers. A number of extensions and modifications have been developed during the last two decades. The reason is surely not that the original algorithm was imperfect or inad­ equate. It is rather the universal applicability and easy handling of the SOM. Com­ pared to many other network paradigms, only a few parameters need to be arranged and thus also for a beginner the network leads to useful and reliable results. Never­ theless there is scope for improvements and sophisticated new developments as this book impressively demonstrates. The number of published applications utilizing the SOM appears to be unending. As the title of this book indicates, the reader will benefit from some of the latest the­ oretical developments and will become acquainted with a number of challenging real-world applications. Our aim in producing this book has been to provide an up­ to-date treatment of the field of self-organizing neural networks, which will be ac­ cessible to researchers, practitioners and graduated students from diverse disciplines in academics and industry. We are very grateful to the father of the SOMs, Professor Teuvo Kohonen for sup­ porting this book and contributing the first chapter.
Reviews about Self-Organizing Neural Networks: Recent Advances and Applications (Studies in Fuzziness and Soft Computing) (2):
kolos
Great book arrived in perfect timing
Tejar
This book seems to be the most recent and comprehensive survey of SOM applications which are described in detail. Really good technical chapters, could have another one or two on financial business. I have never read such a deep chapter on SOM quality measurements. Overall, good complement to Kohonen's bible.

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