文件名称:Wavelet-Entropy
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文中从小波变换的角度出发,通过在尺
度域上对信号能量的一种划分,引入了小波能谱与小波熵作为信号特征提取的特征量来反映系统信号的统计特征。实验结果表明,该算法能有效提取弹丸激波信号特征,速度快、准确率高,而且具有对噪声不敏感的优势。
-Paper, starting from the point of view of the wavelet transform, introduced by a division of the signal energy scale domain, wavelet energy spectrum and wavelet entropy feature as a signal feature extraction amount to reflect the statistical characteristics of the system signals. The experimental results show that the algorithm can effectively extract the the projectile shock signal characteristics, speed, high accuracy, and is not sensitive to noise advantage.
度域上对信号能量的一种划分,引入了小波能谱与小波熵作为信号特征提取的特征量来反映系统信号的统计特征。实验结果表明,该算法能有效提取弹丸激波信号特征,速度快、准确率高,而且具有对噪声不敏感的优势。
-Paper, starting from the point of view of the wavelet transform, introduced by a division of the signal energy scale domain, wavelet energy spectrum and wavelet entropy feature as a signal feature extraction amount to reflect the statistical characteristics of the system signals. The experimental results show that the algorithm can effectively extract the the projectile shock signal characteristics, speed, high accuracy, and is not sensitive to noise advantage.
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基于小波熵的弹丸激波信号特征提取方法研究.caj