Wavelet transform moments for feature extraction from temporal signals

被引:8
作者
Carreno, Ignacio Rodriguez [1 ]
Vuskovic, Marko [2 ]
机构
[1] Univ Publ Navarra, Dept Elect & Elect Engn, Pamplona, Spain
[2] San Diego State Univ, Dept Comp Sci, San Diego, CA 92182 USA
来源
INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS II | 2007年
关键词
pattern recognition; EMG; feature extraction; wavelets; moments; support vector machines;
D O I
10.1007/978-1-4020-5626-0_28
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A new feature extraction method based on five moments applied to three wavelet transform sequences has been proposed and used in classification of prehensile surface EMG patterns. The new method has essentially extended the Englehart's discrete wavelet transform and wavelet packet transform by introducing more efficient feature reduction method that also offered better generalization. The approaches were empirically evaluated on the same set of signals recorded from two real subjects, and by using the same classifier, which was the Vapnik's support vector machine.
引用
收藏
页码:235 / +
页数:3
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