Chaotic time series prediction: From one to another

In this Letter, a new local linear prediction model is proposed to predict a chaotic time series of a component x(t)x(t) by using the chaotic time series of another component y(t)y(t) in the same system with x(t)x(t). Our approach is based on the phase space reconstruction coming from the Takens embedding theorem. To illustrate our results, we present an example of Lorenz system and compare with the performance of the original local linear prediction model.