Wavelet analysis and scaling properties of time series

Details Wavelet analysis and scaling properties of time series Wavelet analysis and scaling properties of time series

2004-12-18

arxiv.org/abs/nlin/0412046v2

Nonlinear Sciences

Chaotic Dynamics

4 pages, 4 figures. Accepted for publication in PRE

Scientific paper

10.1103/PhysRevE.72.046120

We propose a wavelet based method for the characterization of the scaling behavior of non-stationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multi-fractal behavior.

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