Title :
A vector quantization neural network model of partial supervision Fuzzy C-Means
Author :
Yang, Xiyang ; Yu, Fusheng
Author_Institution :
Dept. of Math, Quanzhou Normal Univ., Quanzhou
Abstract :
This paper presents a novel version of partial supervision fuzzy c-means (FCM) algorithm. In order to avoid of achieving local minimum and to improve the computation efficiency, a clustering neural network is designed for the new partial supervision FCM algorithm. We also prove that clustering neural network designed is equivalent to the corresponding new partial supervision FCM algorithm. Meanwhile, the experiments are given out and the results show that the neural network of the new partial supervision FCM algorithm can easily find the global optimization solution, and thus is an effective approach.
Keywords :
fuzzy set theory; neural nets; pattern clustering; vector quantisation; clustering neural network; global optimization; partial supervision fuzzy c-means; vector quantization neural network model; Algorithm design and analysis; Clustering algorithms; Computer networks; Fuzzy neural networks; Fuzzy systems; Laboratories; Mathematics; Neural networks; Vector quantization; Clustering neural network; Fuzzy C-Means(FCM); Partial supervision;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597552