中国物理B ›› 2005, Vol. 14 ›› Issue (1): 49-54.doi: 10.1088/1009-1963/14/1/011

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Local discrete cosine transformation domain Volterra prediction of chaotic time series

肖先赐1, 张家树2, 李恒超2   

  1. (1)Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu,610031,China; (2)Sichuan Province Key Lab of Signal and Information Processing,Southwest Jiaotong University, Chengdu,610031, China
  • 收稿日期:2004-03-04 修回日期:2004-08-23 出版日期:2005-01-20 发布日期:2005-01-20
  • 基金资助:
    Project supported by National Nature Science Foundation of China (Grant No 60276096), Ministry Foundation of China (Grant Nos 41101040404 and 51435080104QT2201), Basic Research Foundation of Southwest Jiaotong University (Grant No 2001B08)

Local discrete cosine transformation domain Volterra prediction of chaotic time series

Zhang Jia-Shu (张家树)a, Li Heng-Chao (李恒超)a, Xiao Xian-Ci (肖先赐)b    

  1. a Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, China; b Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610031,China
  • Received:2004-03-04 Revised:2004-08-23 Online:2005-01-20 Published:2005-01-20
  • Supported by:
    Project supported by National Nature Science Foundation of China (Grant No 60276096), Ministry Foundation of China (Grant Nos 41101040404 and 51435080104QT2201), Basic Research Foundation of Southwest Jiaotong University (Grant No 2001B08)

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摘要： In this paper a local discrete cosine transformation (DCT) domain Volterra prediction method is proposed to predict chaotic time series, where the DCT is used to lessen the complexity of solving the coefficient matrix. Numerical simulation results show that the proposed prediction method can effectively predict chaotic time series and improve the prediction accuracy compared with the traditional local linear prediction methods.

关键词: chaotic time series, local prediction, DCT, phase-space reconstruction

Abstract: In this paper a local discrete cosine transformation (DCT) domain Volterra prediction method is proposed to predict chaotic time series, where the DCT is used to lessen the complexity of solving the coefficient matrix. Numerical simulation results show that the proposed prediction method can effectively predict chaotic time series and improve the prediction accuracy compared with the traditional local linear prediction methods.

Key words: chaotic time series, local prediction, DCT, phase-space reconstruction

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  • 0545