Actually the kernel design in the recognition method based on discrete time - frequency representation is a problem of feature selection from the ambiguity functions to reduce feature dimension.

基于离散时频分布的信号识别方法，将时频核设计问题转化为以信号自模糊函数为原始特征的特征选择问题，以实现特征降维和信号识别。

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This paper mainly introduces that the fault vibrating signal of gears was decomposed into time-frequency domains by double-orthogonal wavelet analysis and the fault feature of gears was picked up.

利用双正交小波基将齿轮的故障振动信号分解到时频域，并提取出齿轮的故障特征。

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In the view of feature signal extraction, the local wave time-frequency analysis and information entropy were used to deal with fault diagnosis.

从特征信号提取的角度出发，采用局域波时频分析和信息熵结合的方法进行往复式压缩机故障诊断。

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