PREDICTING CHAOTIC TIME-SERIES WITH WAVELET NETWORKS

A new technique, wavelet network, is introduced to predict chaotic tim e series. By using this technique, firstly, we make accurate short-ter m predictions of the time series from chaotic attractors. Secondly, we make accurate predictions of the values and bifurcation structures of the time series from dynamical systems whose parameter values are cha nging with time. Finally we predict chaotic attractors by making long- term predictions based on remarkably few data points, where the correl ation dimensions of predicted attractors are calculated and are found to be almost identical to those of actual attractors.