New prediction of chaotic time series based on local Lyapunov exponent  

作　　者：张勇 

机构地区：[1]Department of Mathematics and Computer,Wuhan Polytechnic University

出　　处：《Chinese Physics B》2013年第5期191-197,共7页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China (Grant No. 61201452)

摘　　要：A new method of predicting chaotic time series is presented based on a local Lyapunov exponent, by quantitatively measuring the exponential rate of separation or attraction of two infinitely close trajectories in state space. After recon- structing state space from one-dimensional chaotic time series, neighboring multiple-state vectors of the predicting point are selected to deduce the prediction formula by using the definition of the locaI Lyapunov exponent. Numerical simulations are carded out to test its effectiveness and verify its higher precision over two older methods. The effects of the number of referential state vectors and added noise on forecasting accuracy are also studied numerically.A new method of predicting chaotic time series is presented based on a local Lyapunov exponent, by quantitatively measuring the exponential rate of separation or attraction of two infinitely close trajectories in state space. After recon- structing state space from one-dimensional chaotic time series, neighboring multiple-state vectors of the predicting point are selected to deduce the prediction formula by using the definition of the locaI Lyapunov exponent. Numerical simulations are carded out to test its effectiveness and verify its higher precision over two older methods. The effects of the number of referential state vectors and added noise on forecasting accuracy are also studied numerically.

关 键 词：chaotic time series prediction of chaotic time series local Lyapunov exponent least squaresmethod 

分 类 号：O211.61[理学—概率论与数理统计] O415.5[理学—数学]