IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v553y2020ics0378437120300029.html
   My bibliography  Save this article

Influence of the signal to noise ratio for the estimation of Permutation Entropy

Author

Listed:
  • Traversaro, Francisco
  • Legnani, Walter
  • Redelico, Francisco O.

Abstract

In this paper, the influence of signal to noise ratio in the estimation of Permutation Entropy was studied upon signals obtained by simulations of a chaotic deterministic system. Then, using a bootstrap scheme, we applied hypothesis tests to detect noise in a signal computing the Permutation Entropy. Similarly to recent publications, we found that as the content of noise increases (i.e. the signal to noise ratio decreases), three clearly different dynamics appear: dominant deterministic, deterministic noisy and dominant noisy. To discriminate the limits of these zones, another hypothesis test was applied. Finally, we also show that if a hypothesis test detects changes in the value of Permutation Entropy, it is due to changes in the actual dynamics of the system and not due to the presence of noise in the signal.

Suggested Citation

  • Traversaro, Francisco & Legnani, Walter & Redelico, Francisco O., 2020. "Influence of the signal to noise ratio for the estimation of Permutation Entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    • Handle: RePEc:eee:phsmap:v:553:y:2020:i:c:s0378437120300029
    DOI: 10.1016/j.physa.2020.124134
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120300029
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2020.124134?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Lamberti, P.W & Martin, M.T & Plastino, A & Rosso, O.A, 2004. "Intensive entropic non-triviality measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 119-131.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Borges, João B. & Ramos, Heitor S. & Mini, Raquel A.F. & Rosso, Osvaldo A. & Frery, Alejandro C. & Loureiro, Antonio A.F., 2019. "Learning and distinguishing time series dynamics via ordinal patterns transition graphs," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    3. Mateos, Diego M. & Zozor, Steeve & Olivares, Felipe, 2020. "Contrasting stochasticity with chaos in a permutation Lempel–Ziv complexity — Shannon entropy plane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    4. 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.
    5. Aquino, Andre L.L. & Ramos, Heitor S. & Frery, Alejandro C. & Viana, Leonardo P. & Cavalcante, Tamer S.G. & Rosso, Osvaldo A., 2017. "Characterization of electric load with Information Theory quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 277-284.
    6. 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).
    7. López Pérez, Mario & Mansilla Corona, Ricardo, 2022. "Ordinal synchronization and typical states in high-frequency digital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    8. Fernandes, Leonardo H.S. & de Araujo, Fernando H.A. & Tabak, Benjamin M., 2021. "Insights from the (in)efficiency of Chinese sectoral indices during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    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. Calbet, Xavier & López-Ruiz, Ricardo, 2007. "Extremum complexity distribution of a monodimensional ideal gas out of equilibrium," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 523-530.
    11. Viviane M. Gomes & Joao R. B. Paiva & Marcio R. C. Reis & Gabriel A. Wainer & Wesley P. Calixto, 2019. "Mechanism for Measuring System Complexity Applying Sensitivity Analysis," Complexity, Hindawi, vol. 2019, pages 1-12, April.
    12. Aurelio Fernandez Bariviera & María Belén Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "The (in)visible hand in the Libor market: an information theory approach," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(8), pages 1-9, August.
    13. Araújo, Felipe & Bastos, Lucas & Medeiros, Iago & Rosso, Osvaldo A. & Aquino, Andre L.L. & Rosário, Denis & Cerqueira, Eduardo, 2023. "Characterization of human mobility based on Information Theory quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    14. Dias, João, 2013. "Spanning trees and the Eurozone crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5974-5984.
    15. Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Libor at crossroads: Stochastic switching detection using information theory quantifiers," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 172-182.
    16. Zunino, Luciano & Fernández Bariviera, Aurelio & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2012. "On the efficiency of sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4342-4349.
    17. Rosso, Osvaldo A. & Craig, Hugh & Moscato, Pablo, 2009. "Shakespeare and other English Renaissance authors as characterized by Information Theory complexity quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 916-926.
    18. Zhang, Boyi & Shang, Pengjian & Zhou, Qin, 2021. "The identification of fractional order systems by multiscale multivariate analysis," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    19. Shang, Du & Shang, Pengjian, 2022. "The dependence measurements based on martingale difference correlation and distance correlation: Efficient tools to distinguish different complex systems," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    20. 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.

    More about this item

    Keywords

    Permutation Entropy; Hypothesis test;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:553:y:2020:i:c:s0378437120300029. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.