The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.
该方法首先利用小波变换和主成分分析对故障信号进行预处理，然后用处理后的故障特征数据对小波神经网络进行训练和测试。
The concepts and its filter of wavelet transform are introduced, the application of wavelet as a kind of new analysis tools in unstable signal analysis is presented.
介绍了小波变换的基本概念和滤波特性，给出了小波变换作为一种新的分析工具在非平稳信号分析中的应用方法。
Based on the analysis of wavelet packets and traditional adaptive equalization, an adaptive equalizer structure and its adaptive algorithm, based on wavelet packets transform, are presented.
在分析小波包和传统自适应线性均衡的基础上，提出了一种基于小波包变换的自适应均衡器结构，并给出了相应的自适应均衡算法。
Based on mentioned-above wavelet analysis theories, two-dimension biorthogonal wavelet and the implementation of wavelet transform on discrete images have been discussed.
在以上小波分析理论的基础上进一步讨论了二维正交小波变换和离散图像的小波变换实现。
General functions may be represented as Wavelet series. A kind of stabile, efficient and fast algorithm of Wavelet transform may be gotten through multi-resolution analysis.
一般函数都可以写成小波级数的形式，而由多分辨分析可得到小波的稳定有效快速变换算法。
Wavelet transform is a powerful tool for the analysis of the geophysical data. Therefore it is important to develop the program of wavelet analysis and its application.
小波变换是地球物理数据分析的有力工具，研制小波分析应用程序系统并将其广泛地应用于实际的资料处理和分析，尤其重要。
Probed into the two factors of the signal de-noising effect basing on the wavelet transform basing on the analysis of the theory and methods of the wavelet transform: wavelet function and threshold.
在分析小波变换消噪原理和方法的基础上，研究了影响小波变换消噪效果的两个主要因素：小波基函数和阀值。
The conception of wavelet energy spectrum (WES) is posed by comparing the conservation of total energy in harmonic analysis, power spectrum analysis and wavelet transform.
通过比较傅里叶分析和小波分析中能量守恒公式，提出了小波能量谱的概念。
It can be applied in studying the property of any basic wavelet and learning the theory on the wavelet transform, and also in making some engineering signal analysis.
它即可用于对母小波的研究和对小波理论的学习，也可用于一些工程信号分析。
The new algorithm mainly recurred to the ability of detecting singularity in signal by continuous wavelet transform and multi-resolution analysis of wavelet transform.
算法充分利用连续小波变换探测信号奇异性的能力和小波的多分辨率特性。
The new algorithm mainly recurred to the ability of detecting singularity in signal by continuous wavelet transform and multi-resolution analysis of wavelet transform.
算法充分利用连续小波变换探测信号奇异性的能力和小波的多分辨率特性。
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