MULTI-RESOLUTION LEAST SQUARES SUPPORT VECTOR MACHINES

被引:0
|
作者
Wang Liejun Zhang Taiyi Zhou Yatong (Dept of Information and Communication Eng.
机构
关键词
Support Vector Machines (SVM); Least square method; Multi-Resolution Analysis (MRA); Nonlinear system identification;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Least Squares Support Vector Machines (LS-SVM) is an improvement to the SVM. Combined the LS-SVM with the Multi-Resolution Analysis (MRA),this letter proposes the Multi-resolution LS-SVM (MLS-SVM).The proposed algorithm has the same theoretical framework as MRA but with better approximation ability.At a fixed scale MLS-SVM is a classical LS-SVM,but MLS-SVM can gradually approximate the target function at different scales.In experiments,the MLS-SVM is used for nonlinear system identification,and achieves better identification accuracy.
引用
收藏
页码:701 / 704
页数:4
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