Fig.2 An example of a standard EMD for the 1s-MMG signal (500 sample points).
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The standard EMD decomposes a signal x(𝑡) into N sets of frequency- and amplitude-modulated signal components by employing an iterative process called the sifting algorithm, such asx(𝑡)=Σ𝑐𝑖(𝑡)𝑁𝑖=1+𝑟(𝑡),𝑡=1,…,𝑛,𝑖=1,…,𝑁 (1)where the series {𝑐𝑖(𝑡)}𝑖=1𝑁 is called the intrinsic mode functions (IMFs), which represent the intrinsic oscillations present in the raw signal, and 𝑟(𝑡) is a residual trend of the lower frequency (Fig. 2). In brief, the IMF is extracted from a signal by subtracting the average of the upper and lower envelopes, where the envelopes are respectively generated by concatenating all local maxima and minima.
标准经验模态分解(Empirical Mode Decomposition,EMD)通过采用一种称为筛选算法(sifting algorithm)的迭代过程,将信号x(t)分解为N组频率和振幅调制的信号分量,例如x(𝑡)=Σ𝑐𝑖(𝑡)(i=1到N)+𝑟(𝑡),𝑡=1,…,𝑛,𝑖=1,…,𝑁(1)。其中序列{𝑐𝑖(𝑡)}(i=1到N)被称为本征模态函数(Intrinsic Mode Functions,IMFs),代表原始信号中存在的本征振荡;𝑟(𝑡)是低频的残余趋势(图2)。简言之,IMF通过减去上下包络的平均值从信号中提取,其中包络分别由所有局部极大值和极小值连接生成。



