OPEN EDUCATIONAL RESOURCES

UPA PERPUSTAKAAN UNEJ | NPP. 3509212D1000001

  • Home
  • Admin
  • Select Language :
    Arabic Bengali Brazilian Portuguese English Espanol German Indonesian Japanese Malay Persian Russian Thai Turkish Urdu

Search by :

ALL Author Subject ISBN/ISSN Advanced Search

Last search:

{{tmpObj[k].text}}
Image of Pattern recognition by self-organizing neural networks
Bookmark Share

Text

Pattern recognition by self-organizing neural networks

Carpenter, Gail A. - Personal Name; Grossberg, Stephen, - Personal Name;

Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally important in the fields of cognitive science, neuroscience, artificial intelligence, and neural networks in general.

Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally important in the fields of cognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19 articles take up developments in competitive learning and computational maps, adaptive resonance theory, and specialized architectures and biological connections.

Introductory survey articles provide a framework for understanding the many models involved in various approaches to studying neural networks. These are followed in Part 2 by articles that form the foundation for models of competitive learning and computational mapping, and recent articles by Kohonen, applying them to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designing adaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks, selforganizing pattern recognition systems whose top-down template feedback signals guarantee their stable learning in response to arbitrary sequences of input patterns. In Part 4, articles describe embedding ART modules into larger architectures and provide experimental evidence from neurophysiology, event-related potentials, and psychology that support the prediction that ART mechanisms exist in the brain.

Contributors J.-P. Banquet, G.A. Carpenter, S. Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C. von der Malsburg, C.L. Winter


Availability

No copy data

Detail Information
Series Title
-
Call Number
-
Publisher
Cambridge, Mass. : : MIT Press,., 1991.
Collation
1 online resource (691 pages) :illustrations
Language
English
ISBN/ISSN
9780262269896
Classification
NONE
Content Type
text
Media Type
computer
Carrier Type
online resource
Edition
-
Subject(s)
NEURAL NETWORKS (COMPUTER SCIENCE)
Pattern recognition systems.
Specific Detail Info
-
Statement of Responsibility
edited by Gail A. Carpenter and Stephen Grossberg.
Other Information
Cataloger
Kholif Basri
Source
https://doi.org/10.7551/mitpress/5271.001.0001
Validator
Kholif Basri
Digital Object Identifier (DOI)
-
Journal Volume
-
Journal Issue
-
Subtitle
-
Parallel Title
-
Other version/related

No other version available

File Attachment
  • Pattern Recognition by Self-Organizing Neural Networks
Comments

You must be logged in to post a comment

OPEN EDUCATIONAL RESOURCES

Search

start it by typing one or more keywords for title, author or subject


Select the topic you are interested in
  • Computer Science, Information & General Works
  • Philosophy & Psychology
  • Religion
  • Social Sciences
  • Language
  • Pure Science
  • Applied Sciences
  • Art & Recreation
  • Literature
  • History & Geography
Icons made by Freepik from www.flaticon.com
Advanced Search
Where do you want to share?