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Dispersive graded entropy on computing dynamical complexity

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  • Mukherjee, Sayan
  • Banerjee, Santo
  • Rondoni, Lamberto

Abstract

We propose a phase space based statistical disorder to investigate the dynamical complexity of chaotic models. The statistical disorder is defined by introducing a grade function, inversely maps the mean dispersion of the trajectories in the phase space. We denote the associate entropy by the dispersive graded entropy (DGE). Numerical investigation shows that DGE can quantify the dynamical complexity of discrete as well as continuous chaotic systems. A comparative study is also made with the other phase space based entropy measures. Finally, the proposed measure has been applied on three types of heart rate variability (HRV) signals. The results support the clinical observations related to the dynamics of healthy and congestive hearts.

Suggested Citation

  • Mukherjee, Sayan & Banerjee, Santo & Rondoni, Lamberto, 2018. "Dispersive graded entropy on computing dynamical complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 131-140.
    • Handle: RePEc:eee:phsmap:v:508:y:2018:i:c:p:131-140
    DOI: 10.1016/j.physa.2018.05.006
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    References listed on IDEAS

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    Cited by:

    1. Palit, Sanjay K. & Mukherjee, Sayan, 2021. "A study on dynamics and multiscale complexity of a neuro system," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    2. Yan, Bo & Palit, Sanjay K. & Mukherjee, Sayan & Banerjee, Santo, 2019. "Signature of complexity in time–frequency domain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    3. Das, Parthasakha & Das, Pritha & Mukherjee, Sayan, 2020. "Stochastic dynamics of Michaelis–Menten kinetics based tumor-immune interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).

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