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Chaotic Time Series Analysis

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  • Zonghua Liu

Abstract

Chaotic dynamical systems are ubiquitous in nature and most of them does not have an explicit dynamical equation and can be only understood through the available time series. We here briefly review the basic concepts of time series and its analytic tools, such as dimension, Lyapunov exponent, Hilbert transform, and attractor reconstruction. Then we discuss its applications in a few fields such as the construction of differential equations, identification of synchronization and coupling direction, coherence resonance, and traffic data analysis in Internet.

Suggested Citation

  • Zonghua Liu, 2010. "Chaotic Time Series Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2010, pages 1-31, April.
    • Handle: RePEc:hin:jnlmpe:720190
    DOI: 10.1155/2010/720190
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    Cited by:

    1. Frantisek Kuda & Petr Dlask & Marek Teichmann & Vaclav Beran, 2022. "Time–Cost Schedules and Project–Threats Indication," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    2. Zandi-Mehran, Nazanin & Nazarimehr, Fahimeh & Rajagopal, Karthikeyan & Ghosh, Dibakar & Jafari, Sajad & Chen, Guanrong, 2022. "FFT bifurcation: A tool for spectrum analyzing of dynamical systems," Applied Mathematics and Computation, Elsevier, vol. 422(C).

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