Prediction of Chaotic Time Series Based on Neural Network with Legendre Polynomials

Authors:
Hongwei Wang;Hong Gu
Affiliations:
School of Electronic and Information Engineering, Dalian University of Technology, Dalian, China;School of Electronic and Information Engineering, Dalian University of Technology, Dalian, China
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

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Abstract

In this paper, a modeling method based on the orthogonal function neural network is proposed. Legendre orthogonal polynomials are selected as the basic functions of the neural network. Kalman filtering algorithm with singular value decomposition is used to confirm the parameters of orthogonal function neural network in order to avoid error delivery and error accumulation. To demonstrate the performance of this modeling method, the simulation on Mackey-Glass chaotic time series is performed. The results show that this method provides effective and accurate prediction.