%0 Journal Article
%T Generalized least squares support-vector-machine algorithm and its application<br>一种广义最小二乘支持向量机算法及其应用
%A WU Zong-liang
%A DOU Heng
%A <br>吴宗亮
%A 窦衡
%J 计算机应用
%D 2009
%I 
%X Least Squares Support-Vector-Machines (LS-SVM) algorithm is an efficient project about pattern classification on unclassifiable sample set condition. While dealing with many factual pattern classification problems, this algorithm reflects certain limitation. A generalized LS-SVM algorithm was introduced to further improve the applicability of LS-SVM. This new method was applied to radar range profile's recognition. The experimental results show that this new method can achieve better recognition effect.
%K Least Squares Support Vector Machines (LS-SVM)
%K unclassifiable sample sets
%K radar range profile<br>最小二乘支持向量机
%K 不可分样本集
%K 雷达一维距离像
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=6AC9E94A3683800F64EFE04BF0AAEB67&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=38B194292C032A66&sid=A766A50385B9FB1F&eid=D698D0190A84C2BD&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=6