A New Approach to Modifying Fuzzy ARTMAP Systems

Mu Chun Su, Wei Zhe Lu, Chen Chiung Hsieh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A fuzzy ARTMAP system is a system for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequence of analog or binary input vectors. The original fuzzy ARTMAP system incorporates two fuzzy ART modules and an inter-ART module. Many different approaches have been proposed to modify fuzzy ARTMAP systems. In this paper, we proposed a new approach to modifying a fuzzy ARTMAP system. We referred to the new system as the Modified and Simplified Fuzzy ARTMAP (MSFAM) system. Two data sets were used for demonstrating the performance of the proposed MSFAM systems.

Original languageEnglish
Title of host publication18th International Conference on Computers and Their Applications 2003, CATA 2003
EditorsNarayan C. Debnath
PublisherThe International Society for Computers and Their Applications (ISCA)
Pages59-62
Number of pages4
ISBN (Electronic)9781618395498
StatePublished - 2003
Event18th International Conference on Computers and Their Applications, CATA 2003 - Honolulu, United States
Duration: 26 Mar 200328 Mar 2003

Publication series

Name18th International Conference on Computers and Their Applications 2003, CATA 2003

Conference

Conference18th International Conference on Computers and Their Applications, CATA 2003
Country/TerritoryUnited States
CityHonolulu
Period26/03/0328/03/03

Keywords

  • ART
  • learning algorithm
  • neural networks

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