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Wavelet Filtering of Chaotic Data : Volume 7, Issue 1/2 (30/11/-0001)

By Grzesiak, M.

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Book Id: WPLBN0004019947
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Wavelet Filtering of Chaotic Data : Volume 7, Issue 1/2 (30/11/-0001)  
Author: Grzesiak, M.
Volume: Vol. 7, Issue 1/2
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Grzesiak, M. (-0001). Wavelet Filtering of Chaotic Data : Volume 7, Issue 1/2 (30/11/-0001). Retrieved from

Description: Space Research Center of Polish Academy of Sciences, Warsaw, Poland. Satisfactory method of removing noise from experimental chaotic data is still an open problem. Normally it is necessary to assume certain properties of the noise and dynamics, which one wants to extract, from time series. The wavelet based method of denoising of time series originating from low-dimensional dynamical systems and polluted by the Gaussian white noise is considered. Its efficiency is investigated by comparing the correlation dimension of clean and noisy data generated for some well-known dynamical systems. The wavelet method is contrasted with the singular value decomposition (SVD) and finite impulse response (FIR) filter methods.

Wavelet filtering of chaotic data


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