ICFICE 2017
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
Hybrid RBF Network Structure using FCM and Min-Max Network |
¿µ¹®Á¦¸ñ(English Title) |
Hybrid RBF Network Structure using FCM and Min-Max Network |
ÀúÀÚ(Author) |
Kwang Baek Kim
Doo Heon Song
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¿ø¹®¼ö·Ïó(Citation) |
VOL 09 NO. 01 PP. 0265 ~ 0267 (2017. 06) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
Radical basis Function (RBF) network is a well-known heterogeneous powerful learning structure in solving pattern recognition problems, In this paper, we propose a hybrid RBF network structure that combines Fuzzy C-means clustering (FCM) and Min-Max network learning. Since RBF network is a heterogeneous structure, we can take advantage of two different but powerful learning schemes and solve text/number identification problem efficiently. In the proposed stricture, FCM works between input and middle layer while Min-Max network works between middle and output layer.
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Å°¿öµå(Keyword) |
RBF network
FCM
fuzzy logic
Min-Max network
hybrid structure
pattern recognition
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ÆÄÀÏ÷ºÎ |
PDF ´Ù¿î·Îµå
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