一个是基于EMD的时频分布，另一个是基于EMD的非线性能量算子（NEO）方法，其在癫痫脑电信号的处理中都取得了比较好的效果。
One is a time-frequency distribution based EMD, the other is nonlinear energy operator (NEO) based on EMD, and both of them have good results in epileptic EEG signal processing.
对信号进行局域波分解后，建立基于时频分布的信息熵，以此作为故障识别的参数。
After signal local wave decomposition, the information entropy according to time-frequency distribution was established, and it was used as characteristic parameter for fault recognition.
通过对基于信号特征的径向高斯核时频分布进行改进，提出了一种基于信号特征的自适应核时频分布的改进算法。
An improved algorithm for calculating the signal-dependent adaptive kernel time-frequency distribution is put forward based on the radially-Gaussian signal dependent representation.
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