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《Electronics Optics & Control》 2007-01
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Study on prediction technology of chaotic series

JIANG Bin,CHEN Hang-yong,LI Xiang,WANG Hong-qiang(Institute of Space Electronics Information Technology,National University of Defense Technology,Changsha 410073,China)  
To solve the problem of the prediction of the chaotic series,we studied two prediction methods,one is based on RBF neural network and the other is memory-based predictor.These methods were used respectively to the prediction of Logistic series and Kent series.The simulation results showed that the prediction capability of RBF neural network depends greatly on the number of the input nodes,and the increase of the sample size is in direct proportion to prediction precision only in a certain scope.When the predictive bank number is chosen as the correlation dimension of the system,the average prediction error of the memory-based predictor is small,which also decreases as the sample number increases.
【Fund】: 国防预研项目资助(No.41303040203);; 国家自然科学基金资助(No.60402032)
【CateGory Index】: TP18
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