NON-STATIONARY SIGNAL CLASSIFICATION USING THE UNDECIMATED WAVELET PACKET TRANSFORM

被引：0
|
作者：
Du Plessis, Marthinus C. [1 ]
Olivier, Jan C. [2 ]
机构：
[1] Univ Pretoria, ZA-0002 Pretoria, South Africa
[2] Univ Pretoria, Def Res, CSIR, ZA-0002 Pretoria, South Africa
来源：
PROCEEDINGS OF THE 2010 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION | 2010年
关键词：
Non-stationary signal classification; support vector machines; wavelet packet transform; undecimated wavelet packet transform;
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：
A classifier for non-stationary signals is presented in this paper. A time-frequency signal representation is calculated using the undecimated wavelet packet transform. The classification is performed with a support vector machine. Only the highest valued wavelet coefficients are selected as features in order to reduce the effect of noise. This classifier is compared against a classifier using a Wigner-Ville representation on a wide band non-stationary signal. The classifier based on the undecimated wavelet transform achieved a higher classification accuracy. Using only the largest half of the wavelet coefficients increased the classification accuracy.
引用
收藏
页码：340 / 344
页数：5
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