Nonlinear noise reduction: A case study on experimental data

Holger Kantz, Thomas Schreiber, Ingo Hoffmann, Thorsten Buzug, Gerd Pfister, Leci G. Flepp, Josef Simonet, Remo Badii, and Ernst Brun
Phys. Rev. E 48, 1529 – Published 1 August 1993
PDFExport Citation

Abstract

We apply a recently proposed nonlinear noise-reduction method to time sequences from two different experiments. We demonstrate that it is not difficult to choose the parameters of this algorithm, even though we use no other information about the underlying dynamics than the data themselves. The noise reduction is very robust with respect to changes in the choice of parameters. The reliability of the result is tested by an analysis of the corrections. We discuss the effect of noise reduction on estimates of dimensions, entropies, and Liapunov exponents. For comparison we process one of the sets, densely sampled Taylor-Couette flow data, with a global filter based on singular value decomposition.

  • Received 8 February 1993

DOI:https://doi.org/10.1103/PhysRevE.48.1529

©1993 American Physical Society

Authors & Affiliations

Holger Kantz, Thomas Schreiber, and Ingo Hoffmann

  • Fachbereich Physik, Universität Wuppertal, Gauss-Strasse 20, 5600 Wuppertal 1, Germany

Thorsten Buzug and Gerd Pfister

  • Institut für Angewandte Physik, Universität Kiel, 2300 Kiel 1, Germany

Leci G. Flepp, Josef Simonet, Remo Badii, and Ernst Brun

  • Physik-Institut der Universität, Schönberggasse 9, 8001 Zürich, Switzerland

References (Subscription Required)

Click to Expand
Issue

Vol. 48, Iss. 2 — August 1993

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review E

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×