Nonlinear time series prediction using chaotic neural networks

A nonlinear feedback term is introduced into the evaluation equation of wei ghts of the backpropagation algorithm for neural network, the network becom es a chaotic one. For the purpose of that we can investigate how the differ ent feedback terms affect the process of learning and forecasting, we use t he model to forecast the nonlinear time series which is produced by Makey-G lass equation. By selecting the suitable feedback term, the system can esca pe from the local minima and converge to the global minimum or its approxim ate solutions, and the forecasting results are better than those of backpro pagation algorithm.