Prediction of chaotic time series based on EMD method
基于EMD方法的混沌时间序列预测

In order to improve the nonlinear response prediction precision in a long period, the empirical mode decomposition (EMD) method is introduced in the nonlinear prediction. Here, the EMD method is used to decompose the signal, the rosenstein method is used to calculate the largest Lyapunov exponent (LLE), and then the prediction results are obtained on the basis of the LLE. The simulation results of Duffing equation, Lorenz system and cracked rotor system show that the EMD's signals have smaller LLE than the original signal. In this way, the maximum prediction time of a nonlinear signal can be obtained.