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Tsallis-like information measures and the analysis of complex signals

Author

Listed:
  • Martin, M.T.
  • Plastino, A.R.
  • Plastino, A.

Abstract

A Tsallis-like information measure that elaborates upon those of the Tsallis type is shown to be a rather powerful tool for the analysis of complex, non-stationary signals, as exemplified by the Henon map and EEGs. The ensuing results could be of importance concerning the automatic detection of epileptic spikes.

Suggested Citation

  • Martin, M.T. & Plastino, A.R. & Plastino, A., 2000. "Tsallis-like information measures and the analysis of complex signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 275(1), pages 262-271.
    • Handle: RePEc:eee:phsmap:v:275:y:2000:i:1:p:262-271
    DOI: 10.1016/S0378-4371(99)00424-0
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    Citations

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    Cited by:

    1. Telesca, Luciano & Lovallo, Michele & Ramirez-Rojas, Alejandro & Angulo-Brown, Fernando, 2009. "A nonlinear strategy to reveal seismic precursory signatures in earthquake-related self-potential signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(10), pages 2036-2040.
    2. Nikola Gradojevic & Marko Caric, 2017. "Predicting Systemic Risk with Entropic Indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(1), pages 16-25, January.
    3. Nikola Gradojevic, 2021. "Brexit and foreign exchange market expectations: Could it have been predicted?," Annals of Operations Research, Springer, vol. 297(1), pages 167-189, February.
    4. Gradojevic, Nikola & Gencay, Ramazan, 2008. "Overnight interest rates and aggregate market expectations," Economics Letters, Elsevier, vol. 100(1), pages 27-30, July.
    5. Ashutosh Chamoli & R. Yadav, 2015. "Multifractality in seismic sequences of NW Himalaya," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(1), pages 19-32, May.
    6. A. Plastino & Mario C. Rocca, 2015. "On the Nature of the Tsallis–Fourier Transform," Mathematics, MDPI, vol. 3(3), pages 1-9, July.
    7. Papapetrou, M. & Kugiumtzis, D., 2020. "Tsallis conditional mutual information in investigating long range correlation in symbol sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    8. Antonio Squicciarini & Elio Valero Toranzo & Alejandro Zarzo, 2024. "A Time-Series Feature-Extraction Methodology Based on Multiscale Overlapping Windows, Adaptive KDE, and Continuous Entropic and Information Functionals," Mathematics, MDPI, vol. 12(15), pages 1-21, July.

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