Time Series Analysis with Wavelet Coefficients

Naoki Masuda*, Yasunori Okabe

*この研究の対応する著者

研究成果: Article査読

1 被引用数 (Scopus)

抄録

Time series are conventionally analyzed only in the time domain or only in the frequency domain, and few analyses make use of information in both domains simultaneously. On the other hand, time series analysis based on the wavelet transform has been concentrated on the irregularity detection or the analysis of stochastic processes constructed by the wavelet transform. The wavelet transform is applied to stationarity analysis and predictions in the present paper. Using the wavelet transform, we can decompose time series into frequency components. Consequently, we can extract local information with respect to frequency. We observe the time series in both the time domain and the frequency domain simultaneously. And we connect weak stationarity and prediction methods of original time series to those of each frequency component, accompanied with numeric results.

本文言語English
ページ(範囲)131-160
ページ数30
ジャーナルJapan Journal of Industrial and Applied Mathematics
18
1
DOI
出版ステータスPublished - 2001 2
外部発表はい

ASJC Scopus subject areas

  • 工学(全般)
  • 応用数学

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