Local discrete cosine transformation domain Volterra prediction of chaotic time series
Xiao Xian-Cia, Zhang Jia-Shub, Li Heng-Chaob
a Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu,610031,China; b Sichuan Province Key Lab of Signal and Information Processing,Southwest Jiaotong University, Chengdu,610031, China
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.
Received: 04 March 2004
Revised: 23 August 2004
Published: 20 January 2005
PACS:
0545
Fund: 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)
Cite this article:
Xiao Xian-Ci, Zhang Jia-Shu, Li Heng-Chao Local discrete cosine transformation domain Volterra prediction of chaotic time series 2005 Chin. Phys. 14 49
