Prediction of chaotic time series with wavelet coefficients

Naoki Masuda*, Kazuyuki Aihara

*この研究の対応する著者

研究成果: Article査読

4 被引用数 (Scopus)

抄録

Using the wavelet transform, we can express a time series as a summation of frequency components each of which is localized in the frequency domain. In the present paper, we show that each frequency component given as the wavelet coefficients of a deterministic time series preserves the topological structure of the original dynamical system. We subsequently propose new methods to predict a time series by applying the inverse wavelet transform to predictees of frequency components. Our methods can realize good long-term predictions of deterministic time series contaminated with either high-frequency deterministic noise or white noise.

本文言語English
ページ(範囲)50-59
ページ数10
ジャーナルElectronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)
84
6
DOI
出版ステータスPublished - 2001
外部発表はい

ASJC Scopus subject areas

  • 電子工学および電気工学

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