Improvement of Recognition Performance for the Fuzzy ARTMAP Using Average Learning and Slow Learning

Jae Sul LEE; Chan Geun YOON; Choong Woong LEE

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Jae Sul LEE, Chan Geun YOON, Choong Woong LEE, "Improvement of Recognition Performance for the Fuzzy ARTMAP Using Average Learning and Slow Learning" in IEICE TRANSACTIONS on Fundamentals, vol. E81-A, no. 3, pp. 514-516, March 1998, doi: .
Abstract: A new learning method is proposed to enhance the performances of the fuzzy ARTMAP neural network in the noisy environment. It combines the average learning and slow learning for the weight vectors in the fuzzy ARTMAP. It effectively reduces a category proliferation problem and enhances recognition performance for noisy input patterns.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e81-a_3_514/_p

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@ARTICLE{e81-a_3_514,
author={Jae Sul LEE, Chan Geun YOON, Choong Woong LEE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Improvement of Recognition Performance for the Fuzzy ARTMAP Using Average Learning and Slow Learning},
year={1998},
volume={E81-A},
number={3},
pages={514-516},
abstract={A new learning method is proposed to enhance the performances of the fuzzy ARTMAP neural network in the noisy environment. It combines the average learning and slow learning for the weight vectors in the fuzzy ARTMAP. It effectively reduces a category proliferation problem and enhances recognition performance for noisy input patterns.},
keywords={},
doi={},
ISSN={},
month={March},}

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TY - JOUR
TI - Improvement of Recognition Performance for the Fuzzy ARTMAP Using Average Learning and Slow Learning
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 514
EP - 516
AU - Jae Sul LEE
AU - Chan Geun YOON
AU - Choong Woong LEE
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 1998
AB - A new learning method is proposed to enhance the performances of the fuzzy ARTMAP neural network in the noisy environment. It combines the average learning and slow learning for the weight vectors in the fuzzy ARTMAP. It effectively reduces a category proliferation problem and enhances recognition performance for noisy input patterns.
ER -