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Applications of chaotic time series analysis to signal processing

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1 Author(s)
Downes, P.T. ; E-Syst., Inc., Greenville, TX, USA

Chaotic time series analysis methods are applied to communications signals for characterization. Ergodic invariants of nonlinear physical processes unique to a signal are calculated for signals collected from AM, FM, FSK, and SSB radios. Results include calculation of mutual information, information dimension, and Lyapunov exponents. Positive Lyapunov exponents for all signals are calculated and indicate the presence of low level chaos. A comparison of the Eckmann-Ruelle and Wolf methods for calculating Lyapunov exponents for a signal's time series is presented. Information dimension results show separation of signals of some modulation types at the same frequency

Published in:

Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on

Date of Conference:

26-28 Oct 1992