Order of search in Fuzzy ART and Fuzzy ARTMAP: Effect of the choice parameter

Michael Georgiopoulos, Hans Fernlund, George Bebis, Gregory L. Heileman

Research output: Contribution to journalArticlepeer-review

64 Scopus citations


This paper focuses on two ART architectures, the Fuzzy ART and the Fuzzy ARTMAP. Fuzzy ART is a pattern clustering machine, while Fuzzy ARTMAP is a pattern classification machine. Our study concentrates on the order according to which categories in Fuzzy ART, or the ART(a) model of Fuzzy ARTMAP are chosen. Our work provides a geometrical, and clearer understanding of why, and in what order, these categories are chosen for various ranges of the choice parameter of the Fuzzy ART module. This understanding serves as a powerful tool in developing properties of learning pertaining to these neural network architectures; to strengthen this argument, it is worth mentaining that the order according to which categories are chosen in ART 1 and ARTMAP provided a valuable tool in proving important properties about these architectures.

Original languageEnglish (US)
Pages (from-to)1541-1559
Number of pages19
JournalNeural Networks
Issue number9
StatePublished - Dec 1996
Externally publishedYes


  • Fuzzy ART
  • Fuzzy ARTMAP
  • adaptive resonance theory
  • classification
  • clustering
  • learning
  • neural network

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence


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