In this paper, we compre the time fresuency deconvolution method with the wavelets method. We apply our results on several dynamical systems and show the capability of the wavelet's method to reconstruct the attractor of a chaotic time series? We de-noise different data sets in order to rebuilt their attractor using the wavelets method. Tha applications concern temperatures, wind fluctuations, electricity spot prices and exchange rates.