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New prediction of chaotic time series based on local Lyapunov exponent
Authors:Zhang Yong
Affiliation:Department of Mathematics and Computer, Wuhan Polytechnic University, Wuhan 430024, China
Abstract: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 reconstructing 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 local Lyapunov exponent. Numerical simulations are carried 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.
Keywords:chaotic time series   prediction of chaotic time series   local Lyapunov exponent   least squaresmethod
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