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Proceedings Paper

Mutually recursive method to detect and remove noise in chaotic dynamics
Author(s): Antonio Luigi Perrone; Stefano Boccaletti; Gianfranco Basti; Tito F. Arecchi
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Paper Abstract

Many papers have been published recently about the characterization of time-dependent processes through techniques using wavelet approach. Our work takes into account a particular class of time-dependent processes in nonlinear realm. We want to characterize chaotic dynamics from the standpoint of its unstable periodicities. For this aim we introduce a new technique able to stabilize such unstable orbits. We illustrate this technique both from the theoretical and the experimental standpoint. As a further step, we want to deal with the problem of detecting and removing noise from chaotic dynamics. In this paper, firstly, we show how our technique is able to distinguish with very high sensitivity between a purely chaotic dynamics and a chaotic dynamics with noise even though the noise percentage is very low (of the order of 1 percent only Secondly, we apply our technique to remove noise from this dynamics. Finally, we compare both from the theoretical and experimental standpoint our technique with the well known wavelet technique. This work is a part of 'Skynnet' international project supported by the Italian National Institute for Nuclear Physics (INFN) and partially devoted to the application of new chaotic techniques instantiated in neural architectures for compressing, storing and transmitting information to earth from satellites.

Paper Details

Date Published: 15 March 1994
PDF: 10 pages
Proc. SPIE 2242, Wavelet Applications, (15 March 1994); doi: 10.1117/12.170017
Show Author Affiliations
Antonio Luigi Perrone, Univ. of Rome Tor Vergata and INFN (Italy)
Stefano Boccaletti, Univ. of Florence and INO (Italy)
Gianfranco Basti, Pontifical Gregorian Univ. and INFN (Italy)
Tito F. Arecchi, Univ. of Florence and INO (Italy)


Published in SPIE Proceedings Vol. 2242:
Wavelet Applications
Harold H. Szu, Editor(s)

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