23 May 2005 De-noising with wavelets method in chaotic time series: application in climatology, energy, and finance (Invited Paper)
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Proceedings Volume 5848, Noise and Fluctuations in Econophysics and Finance; (2005) https://doi.org/10.1117/12.620301
Event: SPIE Third International Symposium on Fluctuations and Noise, 2005, Austin, Texas, United States
Abstract
In this paper, in order to de-noise a chaotic signal, we compare the time-frequency deconvolution method with the wavelets method. We apply our results on different dynamical systems and show the capability of wavelets' method to reconstruct the attractor of a chaotic time series. Then, we de-noise different data sets in order to re-built their attractor using the wavelets method. The applications concern temperatures and wind fluctuations, electricity spot prices and financial data sets.
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Dominique Guegan, Dominique Guegan, Kebira Hoummiya, Kebira Hoummiya, "De-noising with wavelets method in chaotic time series: application in climatology, energy, and finance (Invited Paper)", Proc. SPIE 5848, Noise and Fluctuations in Econophysics and Finance, (23 May 2005); doi: 10.1117/12.620301; https://doi.org/10.1117/12.620301
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