So Wavelet packet is always used in the extract the feature of fault.
所以小波包对于故障特征提取有着广泛的应用。
参考来源 - 基于小波神经网络的异步电动机振动故障诊断研究The experiment result shows that the wavelet package can extract the feature waves efficiently.
实验结果表明,小波包技术能有效地提取脑电信号特征波。
参考来源 - 基于小波包技术的EEG信号特征波提取分析Dual-tree complex wavelet pocket transform is dedicated to try to resolve the problem of fault line selection.
本文致力于利用双树复小波包变换来尝试解决小电流接地选线问题。
参考来源 - 复小波包变换及其在小电流接地选线中的应用Wavelet packet decomposition is also used for feature extraction by searching the best basis.
还用小波包分解并寻找最优小波包基进行字符的特征提取。
参考来源 - 基于小波分析的车牌字符识别Both wavelet package and EMD algorithms can be used to decompose pipeline leakage AE signals,but the results are greatly different.
采用小波包分解算法和经验模态分解都可以对管道泄漏声发射信号进行分解,但分解结果却存在一定区别。
参考来源 - 基于小波包和HHT变换的声发射信号分析方法Study the wavelet analysis and wavelet-packet decomposition theory.
研究了小波分析、小波包分解的基本理论，并重点研究了小波基的性能。
参考来源 - 小波分析在往复机械特征提取中的应用研究The filter method of automatic soft-threshold based on optimization wavelet-package is applied on the filtering of signal of impulsive noise in firing-gas jet field of rocket.
提出了基于最优小波包基的自动软阈值滤波方法在单兵肩射式火箭燃气射流脉冲噪声信号滤波中的应用。
参考来源 - 单兵肩射式火箭燃气射流脉冲噪声特性的理论分析与实验研究The effect of the signal processing indicated that the ability of checking out the defect is enhanced, and that the method of the wavelets package is more effectire than the method of wavelet analyses in the aviation component signal processing.
从而验证了小波及小波包分析在航空构件超声检测信号处理中应用的有效性。 而且小波包方法比小波方法的处理效果更为理想。
参考来源 - 航空构件超声检测信号小波分析及小波包分析应用研究·2,447,543篇论文数据，部分数据来源于NoteExpress
最后，抽取小波包直方图作为特征表示并应用直方图相交距离从图像数据库中检索被查询图像。
Finally, the wavelet packet histogram is computed as feature signatures and histogram intersection distance is employed to retrieval queried image from image databases.
传统信号去噪方法常采用门限法对噪声信号的小波或小波包变换做阈值处理以达到去噪的目的。
In traditional denoising methods for signals, we usually use the method of threshold to achieve denoising by the threshold disposing of wavelet packet transform.
最后，基于小波包理论将混沌模型预测的结果予以小波包重构，实现对系统特征参数序列的预测。
Finally, the forecasting results of chaotic models are reconstructed based on wavelet packet theory. By doing so, the forecasting of system feature reference data series can be made.
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