基于未消差小波包变换的非平稳信号分类

M. Plessis, J. Olivier
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引用次数: 0

摘要

本文提出了一种非平稳信号的分类器。利用未消差小波包变换计算时频信号的表示。使用支持向量机进行分类。为了减少噪声的影响,只选取小波系数的最高值作为特征。该分类器与在宽带非平稳信号上使用Wigner-Ville表示的分类器进行比较。基于未消差小波变换的分类器具有较高的分类精度。仅使用小波系数的最大一半可以提高分类精度
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-stationary signal classification using the undecimated wavelet packet transform
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 wideband 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
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