An Improved EMD Algorithm for Self-Adaptive Adjustment of Reference Point Position

Xilin Li, Dongxin Li
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Abstract

Empirical Mode decomposition (EMD), invented by Huang et al., National Aeronautics and Space Administration (NASA), is an advanced signal processing method, which can effectively obtain the time-frequency characteristics of non-stationary signals. However, when the upper and lower envelope of the signal is used to construct the cubic spline curve to separate the signals of different modes, the signal distortion problems such as end effect will appear. On the basis of studying the existing methods of this problem, an adaptive method of extremum point position is proposed in this paper, which can reduce the distortion degree in the extraction process of different mode signals. The method takes full account of the intrinsic characteristics of signals, and the effect is better in a variety of evaluation criteria.
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参考点位置自适应调整的改进EMD算法
经验模态分解(Empirical Mode decomposition, EMD)是由美国国家航空航天局(NASA) Huang等人发明的一种先进的信号处理方法,可以有效地获取非平稳信号的时频特性。然而,当利用信号的上下包络线构造三次样条曲线来分离不同模式的信号时,就会出现端点效应等信号畸变问题。本文在研究该问题现有方法的基础上,提出了一种自适应极值点位置方法,该方法可以降低不同模态信号提取过程中的失真程度。该方法充分考虑了信号的固有特性,在多种评价准则下效果较好。
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