%0 Journal Article
%T Fuzzy Clustering Algorithm with Ranking Features and Identifying Noise Simultaneously<br>具有特征排序功能的鲁棒性模糊聚类方法
%A GAO Jun
%A WANG Shi-Tong
%A <br>皋军
%A 王士同
%J 自动化学报
%D 2009
%I 
%X This paper proposes a weighted fuzzy clustering algorithm (FCA) that can identify the noise of samples and rank the samples' features simultaneously according to their contribution degrees, while realizing clustering efficiently. Therefore, the FCA is robust and can be used to extract the sample's features. Experimental results indicate the above advantages of the FCA.
%K Fuzzy clustering
%K convergence
%K weights
%K robustness<br>模糊聚类
%K 收敛性
%K 权参数
%K 鲁棒性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=865AF10A697FDCA1E0965F628210BFD1&yid=DE12191FBD62783C&vid=6209D9E8050195F5&iid=0B39A22176CE99FB&sid=769BD58726D66E7D&eid=D59111839E7C8BDF&journal_id=0254-4156&journal_name=自动化学报&referenced_num=3&reference_num=0