eemd

说明：  经验模态分解（Empirical Mode Decomposition, EMD）方法是由美国NASA的黄锷博士提出的一种信号分析方法。它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。EMD方法在理论上可以应用于任何类型的信号的分解，因而在处理非平稳及非线性信号序列上具有很高的信噪比，体现出非常明显的优势。
(Empirical Mode Decomposition (EMD) is a signal analysis method proposed by the U.S. NASA s Dr. Huang E. It is based on the time-scale features of the data itself to decompose the signal, there is no need to pre-set any function. EMD method in theory can be applied to any type of signal decomposition and therefore non-stationary and nonlinear signal sequence with high signal-to-noise ratio, reflecting a very distinct advantage.)