This paper presents a new learning method to improve noise tolerance in Fuzzy ART. The two weight vectors: the top-down weight vector and the bottom-up weight vector are differently updated by a weighted sum and a fuzzy AND operation. This method effectively resolves the category proliferation problem without increasing the training epochs in noisy environments.
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Chang Joo LEE, Sang Yun LEE, Choong Woong LEE, "Improvement of Noise Tolerance in Fuzzy ART Using a Weighted Sum and a Fuzzy AND Operation" in IEICE TRANSACTIONS on Fundamentals,
vol. E78-A, no. 10, pp. 1432-1434, October 1995, doi: .
Abstract: This paper presents a new learning method to improve noise tolerance in Fuzzy ART. The two weight vectors: the top-down weight vector and the bottom-up weight vector are differently updated by a weighted sum and a fuzzy AND operation. This method effectively resolves the category proliferation problem without increasing the training epochs in noisy environments.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e78-a_10_1432/_p
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@ARTICLE{e78-a_10_1432,
author={Chang Joo LEE, Sang Yun LEE, Choong Woong LEE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Improvement of Noise Tolerance in Fuzzy ART Using a Weighted Sum and a Fuzzy AND Operation},
year={1995},
volume={E78-A},
number={10},
pages={1432-1434},
abstract={This paper presents a new learning method to improve noise tolerance in Fuzzy ART. The two weight vectors: the top-down weight vector and the bottom-up weight vector are differently updated by a weighted sum and a fuzzy AND operation. This method effectively resolves the category proliferation problem without increasing the training epochs in noisy environments.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - Improvement of Noise Tolerance in Fuzzy ART Using a Weighted Sum and a Fuzzy AND Operation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1432
EP - 1434
AU - Chang Joo LEE
AU - Sang Yun LEE
AU - Choong Woong LEE
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E78-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 1995
AB - This paper presents a new learning method to improve noise tolerance in Fuzzy ART. The two weight vectors: the top-down weight vector and the bottom-up weight vector are differently updated by a weighted sum and a fuzzy AND operation. This method effectively resolves the category proliferation problem without increasing the training epochs in noisy environments.
ER -