Multiscale Estimation to the Parameter of Multidimension Time Series

  • Authors:

  • Cheng-Lin Wen;Guang-Jiang Wang;Chuan-Bo Wen;Zhi-Guo Chen

  • Affiliations:

  • Hangzhou Dianzi university, Hangzhou 310018, China;School of Computer and Information Engineering, Henan University, Kaifeng475001, China;School of Computer and Information Engineering, Henan University, Kaifeng475001, China;School of Computer and Information Engineering, Henan University, Kaifeng475001, China

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
  • Year:
  • 2007

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Abstract

During preceding theory study and engineering application, we dealed with the parameter estimation of one-dimension long memory process actually, and rarely take into account high dimensions. There are few papers about it. In this paper, using the decorrelation property of discrete wavelet transform, high dimension situation (mainly 2D) is simplified to 1D and corresponding referrers are improved according to new idea, combining with matrix transform. So the computation complexity is reduced effectively and estimation precision is satisfied. Some experiment results show that this algorithm has a better general performance.