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Characterizing complexity of non-invertible chaotic maps in the Shannon–Fisher information plane with ordinal patterns

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  • Spichak, David
  • Kupetsky, Audrey
  • Aragoneses, Andrés

Abstract

Being able to distinguish the different types of dynamics present in a given nonlinear system is of great importance in complex dynamics. It allows to characterize the system, find similarities and differences with other nonlinear systems, and classify those dynamical regimes to understand them better. For systems that develop chaos it is not always easy to distinguish determinism from stochasticity. We analyze several non-invertible maps by projecting them on the two-dimensional Fisher–Shannon plane using ordinal patterns. We find that this technique unfolds the complex structure of chaotic systems, showing more details than other methods. It also reveals signatures common to most of the non-invertible maps, and demonstrates its capability to distinguish determinism from stochasticity.

Suggested Citation

  • Spichak, David & Kupetsky, Audrey & Aragoneses, Andrés, 2021. "Characterizing complexity of non-invertible chaotic maps in the Shannon–Fisher information plane with ordinal patterns," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:chsofr:v:142:y:2021:i:c:s0960077920308845
    DOI: 10.1016/j.chaos.2020.110492
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    References listed on IDEAS

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    1. Gonçalves, Bruna Amin & Carpi, Laura & Rosso, Osvaldo A. & Ravetti, Martín G., 2016. "Time series characterization via horizontal visibility graph and Information Theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 93-102.
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    Cited by:

    1. Contreras-Reyes, Javier E., 2021. "Chaotic systems with asymmetric heavy-tailed noise: Application to 3D attractors," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    2. Spichak, David & Aragoneses, Andrés, 2022. "Exploiting the impact of ordering patterns in the Fisher-Shannon complexity plane," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    3. Martins, Adriel M.F. & Fernandes, Leonardo H.S. & Nascimento, Abraão D.C., 2023. "Scientific progress in information theory quantifiers," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    4. Contreras-Reyes, Javier E. & Kharazmi, Omid, 2023. "Belief Fisher–Shannon information plane: Properties, extensions, and applications to time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

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