中文说明：
经验模态分解（Empirical Mode Decomposition，简称EMD))方法被认为是2000年来以傅立叶变换为基础的线性和稳态频谱分析的一个重大突破，该方法是依据数据自身的时间尺度特征来进行信号分解，无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。
English Description：
Empirical mode decomposition (EMD) method is considered to be a major breakthrough in linear and steady-state spectrum analysis based on Fourier transform since 2000. This method decomposes the signal according to the time scale characteristics of the data itself without setting any basis function in advance. This is essentially different from Fourier decomposition and wavelet decomposition based on prior harmonic and wavelet basis functions.