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Randomizing nonlinear maps via symbolic dynamics

Author

Listed:
  • De Micco, L.
  • González, C.M.
  • Larrondo, H.A.
  • Martin, M.T.
  • Plastino, A.
  • Rosso, O.A.

Abstract

Pseudo Random Number Generators (PRNG) have attracted intense attention due to their obvious importance for many branches of science and technology. A randomizing technique is a procedure designed to improve the PRNG randomness degree according the specific requirements. It is obviously important to quantify its effectiveness. In order to classify randomizing techniques based on a symbolic dynamics’ approach, we advance a novel, physically motivated representation based on the statistical properties of chaotic systems. Recourse is made to a plane that has as coordinates (i) the Shannon entropy and (ii) a form of the statistical complexity measure. Each statistical quantifier incorporates a different probability distribution function, generating thus a representation that (i) sheds insight into just how each randomizing technique operates and also (ii) quantifies its effectiveness. Using the Logistic Map and the Three Way Bernoulli Map as typical examples of chaotic dynamics it is shown that our methodology allows for choosing the more convenient randomizing technique in each instance. Comparison with measures of complexity based on diagonal lines on the recurrence plots [N. Marwan, M.C. Romano, M. Thiel, J. Kurths, Phys. Rep. 438 (2007) 237] support the main conclusions of this paper.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:14:p:3373-3383
    DOI: 10.1016/j.physa.2008.02.037
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    Citations

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    Cited by:

    1. Rosso, Osvaldo A. & Carpi, Laura C. & Saco, Patricia M. & Gómez Ravetti, Martín & Plastino, Angelo & Larrondo, Hilda A., 2012. "Causality and the entropy–complexity plane: Robustness and missing ordinal patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 42-55.
    2. Aurelio F. Bariviera & Luciano Zunino & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "Efficiency and credit ratings: a permutation-information-theory analysis," Papers 1509.01839, arXiv.org.
    3. Saco, Patricia M. & Carpi, Laura C. & Figliola, Alejandra & Serrano, Eduardo & Rosso, Osvaldo A., 2010. "Entropy analysis of the dynamics of El Niño/Southern Oscillation during the Holocene," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 5022-5027.
    4. 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.
    5. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    6. 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.
    7. Argyroudis, George S. & Siokis, Fotios M., 2019. "Spillover effects of Great Recession on Hong-Kong’s Real Estate Market: An analysis based on Causality Plane and Tsallis Curves of Complexity–Entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 576-586.
    8. 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.
    9. 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.
    10. Eduarda T. C. Chagas & Marcelo Queiroz‐Oliveira & Osvaldo A. Rosso & Heitor S. Ramos & Cristopher G. S. Freitas & Alejandro C. Frery, 2022. "White Noise Test from Ordinal Patterns in the Entropy–Complexity Plane," International Statistical Review, International Statistical Institute, vol. 90(2), pages 374-396, August.
    11. 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.
    12. 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.
    13. Aurelio F. Bariviera & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "A permutation Information Theory tour through different interest rate maturities: the Libor case," Papers 1509.00217, arXiv.org.
    14. De Micco, L. & Antonelli, M. & Larrondo, H.A., 2017. "Stochastic degradation of the fixed-point version of 2D-chaotic maps," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 477-484.

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