Fuzzy c-Means Clustering Algorithm With Two Layers  

作　　者：谢维信 刘健庄 

机构地区：[1]Department of Electronic Engineering, Xidian University, Xi'an 710071 PRC

出　　处：《Chinese Science Bulletin》1993年第7期608-612,共5页

基　　金：Project supported by the National Natural Science Foundation of China.

摘　　要：1 Introduction In 1973 Dunn first presented the fuzzy c-means (FCM) clustering algorithm, which is an extension of the hard c-means (HCM) clustering algorithm presented by Ball and Hall. Bezdek subsequently generalized Dung’s algorithm and established an infinite family of algorithms with a fuzzy objective function and also presented a theory of convergence for the FCM algorithm. Since then, FCM algorithms have been applied in pattern recognition effectively and widely, such as in clustering, image segmentation, shape analysis, medical diagnosis, feature selection, automatic target recognition, and classifier design. However, further applications of the FCM algorithms are restricted by the time re-

关 键 词：FUZZY CLUSTERING FUZZY SETS PATTERN recognition. 

分 类 号：N[自然科学总论]