Self-Organizing Map Formation

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Self-Organizing Map Formation

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Contributions Klaus Obermayer (Editor)
Terrence J. Sejnowski (Editor)
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Edition Name 1st edition
First Sentence Linsker (1986, 1988) has studied by simulation the evolution of weight vectors under a Hebb-type teacherless learning rule in a feedforward linear network.
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Isbn10 0262650606
Isbn13 9780262650601
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Languages /languages/eng
Latest Revision 5
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Number Of Pages 415
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Physical Dimensions 8.7 x 5.9 x 0.8 inches
Physical Format Paperback
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Publish Date October 1, 2001
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Publishers The MIT Press
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Revision 5
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Subjects General Theory of Computing
Neural Networks
Neurosciences
Mathematical Statistics
Neural Computing
Computers
Computers - General Information
Computer Books: General
General
Neuroscience
Medical / Neuroscience
Probability & Statistics - General
Neural computers
Neural networks (Computer scie
Neural networks (Computer science)
Self-organizing maps
Subtitle Foundations of Neural Computation (Computational Neuroscience)
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Title Self-Organizing Map Formation
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Weight 1.4 pounds
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Self-Organizing Map Formation
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Authors Klaus Obermayer
Terrence Joseph Sejnowski
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Categories Computers
Content Version 0.1.1.0.preview.1
Description This book provides an overview of self-organizing map formation, including recent developments. Self-organizing maps form a branch of unsupervised learning, which is the study of what can be determined about the statistical properties of input data without explicit feedback from a teacher. The articles are drawn from the journal Neural Computation.The book consists of five sections. The first section looks at attempts to model the organization of cortical maps and at the theory and applications of the related artificial neural network algorithms. The second section analyzes topographic maps and their formation via objective functions. The third section discusses cortical maps of stimulus features. The fourth section discusses self-organizing maps for unsupervised data analysis. The fifth section discusses extensions of self-organizing maps, including two surprising applications of mapping algorithms to standard computer science problems: combinatorial optimization and sorting.Contributors J. J. Atick, H. G. Barrow, H. U. Bauer, C. M. Bishop, H. J. Bray, J. Bruske, J. M. L. Budd, M. Budinich, V. Cherkassky, J. Cowan, R. Durbin, E. Erwin, G. J. Goodhill, T. Graepel, D. Grier, S. Kaski, T. Kohonen, H. Lappalainen, Z. Li, J. Lin, R. Linsker, S. P. Luttrell, D. J. C. MacKay, K. D. Miller, G. Mitchison, F. Mulier, K. Obermayer, C. Piepenbrock, H. Ritter, K. Schulten, T. J. Sejnowski, S. Smirnakis, G. Sommer, M. Svensen, R. Szeliski, A. Utsugi, C. K. I. Williams, L. Wiskott, L. Xu, A. Yuille, J. Zhang.
Language en
Maturity Rating NOT_MATURE
Page Count 440
Print Type BOOK
Published Date 2001
Publisher MIT Press
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Subtitle Foundations of Neural Computation
Title Self-organizing Map Formation
ISBN_100262650606
ISBN_139780262650601

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