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Proceedings Paper

Detection of chaos based on wavelet transform
Author(s): Yaojun Wu; Baoqi Tao
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Paper Abstract

The method in which the wavelet transform and fractal theories are applied to detect chaotic signals with the additive observed noises is presented in this paper. Smoothing operator is derived from wavelet transform and used to process the chaotic time series. According to its character of no-scale interval in certain scales, a detected example of the noisy chaotic behavior produced by a Lorenz attractor is provided by using the improved G-P algorithm to calculate its fractal dimension. The results shows that the method introduced here expresses a good ability to detect chaos.

Paper Details

Date Published: 23 October 1996
PDF: 9 pages
Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); doi: 10.1117/12.255303
Show Author Affiliations
Yaojun Wu, Nanjing Univ. of Aeronautics and Astronautics (China)
Baoqi Tao, Nanjing Univ. of Aeronautics and Astronautics (China)


Published in SPIE Proceedings Vol. 2825:
Wavelet Applications in Signal and Image Processing IV
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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