An adaptive approach based on Bernstein polynomial to predict chaotic time series
基于Bernstein多项式的自适应混沌时间序列预测算法

In this paper, we propose an approach using the Bernstein polynomial to model the dynamics of chaotic time series. Combining it with RLS algorithm, we can predict the chaotic time series adaptively. Theoretical analysis and computer simulation have demonstrated that this approach can provide high precision and satisfactory percentage of prediction for some typical chaotic time series. Because of the fast convergence of RLS algorithm, this approach can be applied to predicting short record chaotic time series in real time.