文中提出了首先用小波分析方法提取出瞬态信号的各级小波分解能量，然后再用r BF神经网络对提取的特征向量进行分类。
At first, all levels energy of wavelet decomposed in the transient are extracted by the means of wavelet analysis, then the extracted feature vectors are classified with RBF neural network.
应用小波包分解及其能量谱直观地识别出故障的特征频带，并进行了量化分析。
The characteristic frequency band of the fault can be identified by wavelet packet decomposition and its energy spectrum conveniently, and the quantification analysis are then performed.
应用小波包分解及其能量谱直观地识别出故障的特征频带，并进行了量化分析。
The characteristic frequency band of the fault could be identified by wavelet packet decomposition and its energy spectrum conveniently, at the same time, quantification analysis were performed.
本文采用连续化的数学模型和能量变分解，对超高层圆形网筒结构的静力、动力特性和整体稳定性进行分析。
The static, dynamic characteristic and monolithic stability analysis of the circular latticed-tube structure are discussed in this paper.
利用子波变换的多尺度分析原理，将原始光谱数据分解成集中源信号绝大部分能量的模糊信号和反映源信号变化特性的锐化信号。
Using the principle of multi-resolution analysis, we decompose a set of original spectral data into the blurring signal part and the sharpening signal part.
目的使用能量变换与小波分解的联合算法检测心电信号QRS波群的特征点，为心电信号的自动分析提供新的手段。
Objective To find a new method for ECG autoanalysis of through the combination of energy transform and wavelet decomposition for detecting the characteristic point of QRS complex.
分析了用小波包能量分析方法提取故障信号特征向量的方法，并改进算法解决了小波包分解中的混频现象，根据最佳分解树进行了特征选择。
Based on the frequency domain feature, energy eigenvector of frequency domain is presented using wavelet packet analysis method, and the way of best tree is used to choose symptom.
分析了用小波包能量分析方法提取故障信号特征向量的方法，并改进算法解决了小波包分解中的混频现象，根据最佳分解树进行了特征选择。
Based on the frequency domain feature, energy eigenvector of frequency domain is presented using wavelet packet analysis method, and the way of best tree is used to choose symptom.
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