%0 Journal Article
%T Adaptive blind source separation algorithm based on vicinal risk minimizing PDF estimation<br>基于邻域风险最小化概率密度估计的自适应盲分离算法*
%A LUAN Hai-yan
%A JIANG Hu
%A LUO Jun
%A <br>栾海妍
%A 江桦
%A 罗军
%J 计算机应用研究
%D 2010
%I 
%X The paper studied the vicinal risk minimization based PDF estimation algorithm using support vector machine, and proposed a new construction algorithm for the vicinity function. Combining with natural gradient batch algorithm, put forward a new adaptive blind source separation algorithm. Analyzed the precision of the solution farther using the generalized gauss mo-del. Carried out the several experiments, which proved that the algorithm could separate the mixtures containing signals with different statistical characteristic. Compared with the widely algorithm based on expirical risk minimization methods, the proposed algorithm has better performance both in the convergent speed and the precision.
%K vicinal risk
%K estimation of probability density function
%K support vector machine
%K activate function
%K natural gra-dient algorithm
%K blind source separation<br>邻域风险
%K 概率密度估计
%K 支持向量机
%K 激活函数
%K 自然梯度算法
%K 盲分离
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=FC2D8A3503F17239BECE8F72A5490610&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=5D311CA918CA9A03&sid=A0157EB1E2B4EC8F&eid=6C53EC93BB68E3BC&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=19