| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 724136 | IFAC Proceedings Volumes | 2006 | 6 Pages |
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.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
