Chaotic Time Series Prediction Using Wavelet Decomposition
نویسنده
چکیده
A novel approach to chaotic time series prediction is proposed. It is based on the use of the Discrete Wavelet Transform for obtaining a proper decomposition of the original sequence and standard multilayer neural networks for performing the prediction of the individual components. Simulation results for the case of chaotic signals obtained by integrating the Lorenz equations are presented, and directions for further research are outlined.
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تاریخ انتشار 2002