本文通过分析经验模式分解方法的原理，对其关键技术进行研究并提出了一种改进算法。
This paper analyzes the principle of empirical mode decomposition method, and it analyzes key technologies and proposed an improved algorithm.
经验模式分解（EMD）通过筛分过程将原始信号分解成若干个基本模式分量（IMF），可看作无需预设带宽的自适应高通滤波方法。
Empirical mode decomposition(EMD) is a signal processing technique to decompose data set into several intrinsic mode functions(IMF) by a sifting process.
在论述了经验模式分解（EMD）信号分解原理的基础上，分析了其存在的边缘效应，并提出了通过添加极值点抑制边缘效应的思路和策略。
The end effects of empirical mode decomposition (EMD) are discussed and the end effects are restrained by the method. The results of EMD in both signals are analyzed by three ways.
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