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| Titel |
Wavelet filtering of chaotic data |
| VerfasserIn |
M. Grzesiak |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 7, no. 1/2 ; Nr. 7, no. 1/2, S.111-116 |
| Datensatznummer |
250004247
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| Publikation (Nr.) |
 copernicus.org/npg-7-111-2000.pdf |
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| Zusammenfassung |
| 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. |
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