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Info-quantifiers’ map-characterization revisited

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  • Rosso, Osvaldo A.
  • De Micco, Luciana
  • Plastino, A.
  • Larrondo, Hilda A.

Abstract

We highlight the potentiality of a special Information Theory (IT) approach in order to unravel the intricacies of nonlinear dynamics, the methodology being illustrated with reference to the logistic map. A rather surprising dynamic feature→plane-topography map becomes available.

Suggested Citation

  • Rosso, Osvaldo A. & De Micco, Luciana & Plastino, A. & Larrondo, Hilda A., 2010. "Info-quantifiers’ map-characterization revisited," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4604-4612.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:21:p:4604-4612
    DOI: 10.1016/j.physa.2010.06.055
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    References listed on IDEAS

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    1. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2009. "Forbidden patterns, permutation entropy and stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2854-2864.
    2. O. A. Rosso & C. Masoller, 2009. "Detecting and quantifying temporal correlations in stochastic resonance via information theory measures," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 69(1), pages 37-43, May.
    3. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    4. Zunino, L. & Pérez, D.G. & Kowalski, A. & Martín, M.T. & Garavaglia, M. & Plastino, A. & Rosso, O.A., 2008. "Fractional Brownian motion, fractional Gaussian noise, and Tsallis permutation entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6057-6068.
    5. Keller, K. & Sinn, M., 2005. "Ordinal analysis of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 356(1), pages 114-120.
    6. Rosso, Osvaldo A & Mairal, Marı́a Liliana, 2002. "Characterization of time dynamical evolution of electroencephalographic epileptic records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 469-504.
    7. De Micco, L. & González, C.M. & Larrondo, H.A. & Martin, M.T. & Plastino, A. & Rosso, O.A., 2008. "Randomizing nonlinear maps via symbolic dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3373-3383.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. 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).
    2. Montani, Fernando & Deleglise, Emilia B. & Rosso, Osvaldo A., 2014. "Efficiency characterization of a large neuronal network: A causal information approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 58-70.
    3. Kowalski, A.M. & Martín, M.T. & Plastino, A. & Rosso, O.A., 2011. "Fisher information description of the classical–quantal transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2435-2441.
    4. De Micco, Luciana & Fernández, Juana Graciela & Larrondo, Hilda A. & Plastino, Angelo & Rosso, Osvaldo A., 2012. "Sampling period, statistical complexity, and chaotic attractors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2564-2575.
    5. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M. & Neto, Jusie S.P., 2021. "Macroeconophysics indicator of economic efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    6. Baravalle, Roman & Rosso, Osvaldo A. & Montani, Fernando, 2017. "A path integral approach to the Hodgkin–Huxley model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 986-999.
    7. Montangie, Lisandro & Montani, Fernando, 2015. "Quantifying higher-order correlations in a neuronal pool," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 388-400.
    8. Olivares, Felipe & Plastino, Angelo & Rosso, Osvaldo A., 2012. "Ambiguities in Bandt–Pompe’s methodology for local entropic quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2518-2526.
    9. Aurelio F. Bariviera & Luciano Zunino & Osvaldo A. Rosso, 2016. "Crude Oil Market And Geopolitical Events: An Analysis Based On Information-Theory-Based Quantifiers," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 21(1), pages 41-51, May.
    10. Mateos, Diego M. & Gómez-Ramírez, Jaime & Rosso, Osvaldo A., 2021. "Using time causal quantifiers to characterize sleep stages," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    11. Baravalle, Roman & Rosso, Osvaldo A. & Montani, Fernando, 2018. "Discriminating imagined and non-imagined tasks in the motor cortex area: Entropy-complexity plane with a wavelet decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 27-39.

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