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Local discrete cosine transformation domain Volterra prediction of chaotic time series

         

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.

著录项

  • 来源
    《中国物理:英文版》 |2005年第1期|49-54|共6页
  • 作者

    张家树; 李恒超; 肖先赐;

  • 作者单位

    Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, China;

    Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, China;

    Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610031, China;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类
  • 关键词

    chaotic time series; local prediction; DCT; phase-space reconstruction;

    机译:混沌时间序列局部预测DCT相空间重构;
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