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Adaptive Resonance Theory Algorithms

  • Teresa Serrano-Gotarredona
  • Bernabé Linares-Barranco
  • Andreas G. Andreou
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 456)

Abstract

Adaptive Resonance Theory is a well established neural network framework, developed at the Center for Adaptive Systems of Boston University. It is based on a solid study of mathematical models developed during many years [Grossberg, 1976], [Grossberg, 1980], [Carpenter, 1991a] and which made possible the invention of a series of architectures of Adaptive Resonance Theory (ART). There is an extensive variety of ART architectures. Furthermore, new architectures are being reported as we write these lines, and certainly more will appear in the future.

Keywords

Input Vector Input Pattern Class Vector ART1 Module Complement Code 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Teresa Serrano-Gotarredona
    • 1
  • Bernabé Linares-Barranco
    • 1
  • Andreas G. Andreou
    • 2
  1. 1.National Microelectronics CenterSevillaSpain
  2. 2.The Johns Hopkins UniversityUSA

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