%0 Journal Article
%T Method of nonlinear character extraction in communication traffic based on KPCA<br>一种基于核主元分析的话务量特征提取方法*
%A ZHONG Bing-xiang
%A LI Tai-fu
%A WANG De-biao
%A SU Ying-ying
%A <br>钟秉翔
%A 李太福
%A 汪德彪
%A 苏盈盈
%J 计算机应用研究
%D 2010
%I 
%X In view of the communication traffic feature, this paper presented a method of nonlinear character extraction based on kernel function principal component analysis(KPCA). Nonlinear character extracted by KPCA reflectd the complex relationship between original input and output data and simplified the array dimension of input data. By comparing simulation results, the prediction model based on KPCA-RBFNN has better ability to deal with nonlinear data than that prediction model based on PCA-RBFNN. The experimental results show that this method is very effective.
%K communication traffic
%K character extraction
%K kernel function
%K principal component analysis
%K RBFNN<br>话务量
%K 特征提取
%K 核函数
%K 主元分析
%K 神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=B217FF9E747ACCC92D56B76CC7CD94AF&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=B31275AF3241DB2D&sid=4B5EFEE8F5D7C671&eid=FEED338A3909FFE2&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10