Chaotic time series prediction using the Kohonen algorithm
نویسندگان
چکیده
Deterministic nonlinear prediction is a pow erful tec hnique for the analysis and prediction of time series generated by nonlinear dynamical systems. In this paper the use of a Kohonen netw ork asa component of one deterministic nonlinear prediction algorithm is suggested. In order to evaluate the performance of the proposed algorithm, it was applied to the prediction of time series generated by two well known c haotic dynamical systems and the results were compared with those obtained using the Modi ed Method of Analogues with the same time series. The generated time series were corrupted by superimposed observational noise. The experimental results ha ve sho wn that the Kohonen net w ork can learn the neigh borhood relations present in the reconstructed attractor of the time series and that good predictions can also be obtained with the proposed
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