%0 Journal Article
%T KPCA feature extraction based on CBPSO algorithm
基于文化粒子群算法的KPCA特征提取*
%A ZHAO Min
%A YANG Hui-xian
%A OU Xun-yong
%A
赵 敏
%A 杨恢先
%A 欧训勇
%J 计算机应用研究
%D 2009
%I
%X How to choose the best or near kernel function to reduce test error rate is the key of KPCA applied to feature extraction.In order to the optimization of kernel function,increased the ability of feature extraction and decrease the test error rate,on the basis of research of CA,PSO,this paper proposed a program flow of CBPSO used for training kernel function and built CBPSO-KPCA.This approach could effectively optimize kernel function.Compared CBPSO-KPCA simulation results with GA-KPCA simulation results,it ...
%K CA
%K PSO
%K CBPSO
%K kernel principle component analysis (KPCA)
%K feature extraction
%K GA
文化算法
%K 粒子群优化
%K 文化粒子群算法
%K 核主分量分析
%K 特征提取
%K 遗传算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=3D6B8EDB824827DBE8DE350067A4B67E&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=5D311CA918CA9A03&sid=6F6DB7E6345096DE&eid=52DD94C3323CD74D&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=1&reference_num=8