关于经验模态分解与整体经验模态分解的分离效果差别的探讨

A Study on the Different Separation Effect between EMD and EEMD

经验模态分解(Empirical Mode Decomposition,简称EMD)是一种自适应信号分解方法,主要应用于非线性非平稳的信号。整体平均经验模态分解(Ensemble Empirical Mode Decomposition,简称EEMD)解决了EMD中出现的模态混合问题。在此主要讨论EMD和EEMD处理含噪信号时的效果差异,就几种特殊的信号,对EMD和EEMD在实际应用中出现的问题进行探讨。

Empirical Mode Decomposition（EMD） is kind of adaptive decomposition method and it is mainly applied to nonlinear and non-stationary signals.Ensemble Empirical Mode Decomposition（EEMD） method was raised to solve the issue of mixed mode in the traditional Empirical Mode Decomposition.The different effects of EMD and EEMD is mainly discussed to the noisy signal.It talked about some problems in applications of EMD and EEMD through particular examples.