Minimal Error Rate Classification in a Non-stationary Environment via a Modified Fuzzy ARTMAP Network

  • Chee Peng Lim
  • Robert F. Harrison
Conference paper


This paper investigates the feasibility of the fuzzy ARTMAP neural network for statistical classification and learning tasks in an on-line setting. The inability of fuzzy ARTMAP in implementing a one-to-many mapping is explained. Thus, we propose a modification and a frequency measure scheme which tend to minimise the misclassification rates. The performance of the modified network is assessed with noisy pattern sets in both stationary and non-stationary environments. Simulation results demonstrate that modified fuzzy ARTMAP is capable of learning in a changing environment and, at the same time, of producing classification results which asymptotically approach the Bayes optimal limits. The implications of taking time averages, rather than ensemble averages, when calculating performance statistics are also studied.


Input Vector Input Pattern Small Standard Deviation Target Output Misclassification Rate 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Cybenko, G.: Mathematics of Control, Signals and Systems, 2, pp 303. (1989).MathSciNetMATHCrossRefGoogle Scholar
  2. [2]
    Girosi, F., Poggio, T.: Biological Cybernetics, 63, pp 169. (1990).MathSciNetMATHCrossRefGoogle Scholar
  3. [3]
    Carpenter, G.A., Grossberg, S.: Computer Vision, Graphics and Image Processing, 37, pp 54. (1987).CrossRefGoogle Scholar
  4. [4]
    Carpenter, G.A., Grossberg, S.: IEEE Computer, 21, pp 77. (1988).CrossRefGoogle Scholar
  5. [5]
    Carpenter, G.A., Grossberg, S., Maikuzon, N., Reynolds, J.H., Rosen, D.B.: IEEE Trans, on Neural Networks, 3 (5), pp 698. (1992).CrossRefGoogle Scholar
  6. [6]
    Carpenter, G.A., Grossberg, S., Reynolds, J.H.: Neural Networks, 4, pp 565. (1991).CrossRefGoogle Scholar
  7. [7]
    Carpenter, G.A., Grossberg, S., Rosen, D.B.: Neural Networks, 4, pp 759. (1991).CrossRefGoogle Scholar
  8. [8]
    Moore, B.: Proc. 1988 Connectionist Models Summer School, pp 174. (1988).Google Scholar
  9. [9]
    Zadeh, L.: Information and Control, 8, pp 338. (1965).MathSciNetMATHCrossRefGoogle Scholar
  10. [10]
    Lim, C.P., Harrison, R.F.: To appear in Neural Networks.Google Scholar

Copyright information

© Springer-Verlag/Wien 1995

Authors and Affiliations

  • Chee Peng Lim
    • 1
  • Robert F. Harrison
    • 1
  1. 1.Department of Automatic Control and Systems EngineeringThe University of SheffieldSheffieldUK

Personalised recommendations