基于多项式拟合算法的EMD端点问题的处理

经验模态分解(EMD)是由Huang等发展的一种新的数据分析方法,但是在利用样条插值获得上下包络过程中存在着棘手的端点问题。文章在解决该问题已有算法的基础上,提出了多项式拟合算法。它利用多项式来拟合临近端点处的极值点序列,再由此多项式求出极值点序列在端点处的近似取值,使得对极值点进行插值的三次样条在端点处不会发生大的摆动。通过对三种算法进行比较,证明了多项式拟合算法可以有效地抑制端点效应。

Dealing with the End Issue of EMD Based on Polynomial Fitting Algorithm

The Empirical Mode Decomposition(EMD)is a new method for data analysis developed by Huang etc.But there is an involved end issue in the course of getting two envelops of the data using spline interpolation.In this paper,on the basis of existing algorithms for solving the problem,a new method which utilizes polynomial fitting is proposed.It fits the extrema sequence near the ends of the data with a polynomial,gets the approximation on the ends of the extrema sequence through the polynomial,and the cubic spline which interpolates the extrema doesn't swing widely at both ends of the data.By means of comparing three different methods,it is proved that the new method can be used to solve the end issue effectively.