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Learning method for fuzzy ARTMAP in a noisy environment

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3 Author(s)
J. S. Lee ; Coll. of Eng., Seoul Nat. Univ., South Korea ; C. G. Yoon ; C. W. Lee

A new learning method is proposed to enhance the performances of fuzzy adaptive resonance theory-predictive mapping (ARTMAP) neural networks in a noisy environment. It combines the average learning and slow learning for the weight vectors in fuzzy ARTMAP. It effectively reduces a category proliferation problem, and enhances recognition performance for noisy input patterns

Published in:

Electronics Letters  (Volume:34 ,  Issue: 1 )