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Indexed by:会议论文

Date of Publication:2012-07-15

Included Journals:EI、Scopus

Page Number:298-301

Abstract:In this paper, a single-layer orthogonal neural network (ONN) which is developed based on orthogonal functions is introduced. Since the processing elements are orthogonal to one another and there is no local minimum of error function, the orthogonal neural network is able to avoid the above problems. Legendred orthogonal polynomial functions are selected as the basic functions of the orthogonal function neural network. Kalman filtering algorithm with singular value decomposition is used to confirm the parameters and weights of the 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. ? 2012 IEEE.