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发布时间：2019-03-11

论文类型：期刊论文

发表时间：2009-05-26

发表刊物：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录刊物：Scopus、CPCI-S、EI

卷号：5551 LNCS

期号：PART 1

页面范围：836-843

ISSN号：3642015069

关键字：Neural network; Legendre orthogonal polynomials; Kalman filtering; Singular value decomposition; Chaotic time series

摘要：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. © 2009 Springer Berlin Heidelberg.