Sparse approximation based on wavelet kernel support vector machines

被引：0
|
作者：
Yang, DK [1 ]
Tong, YB [1 ]
Zhang, QS [1 ]
机构：
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100083, Peoples R China
来源：
PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9 | 2005年
关键词：
wavelet kernel function; support vector machine; sparse approximation;
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：
For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel support vector machines, which can converge to minimum error with better sparsity. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.
引用
收藏
页码：4249 / 4253
页数：5
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