Research on fuzzy kohonen neural network for fuzzy clustering

Authors:
ShuiSheng Ye;XiaoLin Qin;Hong Cai
Affiliations:
Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Jiangsu, P.R. China;Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Jiangsu, P.R. China;Nanchang Institute of Aeronautical Technology, Jiangxi, P.R. China
Venue:
CDVE'06 Proceedings of the Third international conference on Cooperative Design, Visualization, and Engineering
Year:
2006

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Abstract

A model of fuzzy Kohonen neural network for fuzzy clustering is presented. It uses fuzzy membership degree to describe approximate degree for input patterns and clusters’ centers, which is represented by learning rate. In addition, in order to extract more useful information from input patterns, a supervised learning, called post-learning phase, is added to adaptive learning. Then the model is applied for a specific clustering’s problem, the result shows it can greatly improve performances of recognition and classification.