局部投影算法及其在非线性时间序列分析中的应用

引入了非线性时间序列的局部投影消噪算法。该算法将时间序列先进行相重构,在高维的相空间上采用局部投影的方法将相空间分解成正交的子空间,来分离时序中不同的分量。通过Lorenz模型的数值仿真分析,证实了该算法在消除非线性时间序列中随机噪声的效果。此外还讨论了局部投影算法在提取微弱特征信号中的应用。

LOCAL PROJECTIVE METHOD AND IT'S APPLICATION ON NONLINEAR TIME SERIES

A local projective noise reduction for nonlinear time series is here introduced. First, one would reconstruct the time series using delay coordinates. In the high dimensional phase space, the local projective algorithm is used to separate it into different components in the time series by dividing the phase space into orthogonal sub-spaces. Though numerical simulations of Lorenz model, it is proved that the algorithm has an excellent effect on removing random noise in nonlinear time series. Furthermore, two algorithms of extracting weak feature signals from a time series are discussed.