%0 Journal Article
%T Feature extraction based on kernel function and application of improved methods<br>一种基于核函数特征提取改进方法的应用
%A LI De-qi
%A LIU Chuan-ling
%A <br>李德启
%A 刘传领
%J 计算机应用研究
%D 2011
%I 
%X For the standard KCCA method in the case of training samples increases the complexity of the corresponding surge in the computer memory occupied by a large quantity of defects,based on the standard derivation of KCCA feature extraction methods,this paper proposed an improved feature extraction method of nuclear function.In this method,the value based on characteristics of the training sample size to judge the degree of importance,and then completed the corresponding eigenvectors,and combined with the SVDD c...
%K kernel canonical correlation analysis(KCCA)
%K feature extraction
%K computational complexity
%K memory footprint
%K recognition rate<br>核典型相关分析
%K 特征提取
%K 计算复杂度
%K 内存占用量
%K 识别率
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F32C7DEF351C88CCD0BE91FB6B54E7FF&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=5D311CA918CA9A03&sid=F96FF7A54D43FC82&eid=8424FD92DE0D1368&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=36