IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0117365.html
   My bibliography  Save this article

The Complexity of Sequences Generated by the Arc-Fractal System

Author

Listed:
  • Hoai Nguyen Huynh
  • Andri Pradana
  • Lock Yue Chew

Abstract

We study properties of the symbolic sequences extracted from the fractals generated by the arc-fractal system introduced earlier by Huynh and Chew. The sequences consist of only a few symbols yet possess several nontrivial properties. First using an operator approach, we show that the sequences are not periodic, even though they are constructed from very simple rules. Second by employing the ϵ-machine approach developed by Crutchfield and Young, we measure the complexity and randomness of the sequences and show that they are indeed complex, i.e. neither periodic nor random, with the value of complexity measure being significant as compared to the known example of logistic map at the edge of chaos. The complexity and randomness of the sequences are then discussed in relation with the properties of associated fractal objects, such as their fractal dimension, symmetry and orientations of the arcs.

Suggested Citation

  • Hoai Nguyen Huynh & Andri Pradana & Lock Yue Chew, 2015. "The Complexity of Sequences Generated by the Arc-Fractal System," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-21, February.
  • Handle: RePEc:plo:pone00:0117365
    DOI: 10.1371/journal.pone.0117365
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0117365
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0117365&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0117365?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
    ---><---

    References listed on IDEAS

    as
    1. Haroldo V Ribeiro & Luciano Zunino & Ervin K Lenzi & Perseu A Santoro & Renio S Mendes, 2012. "Complexity-Entropy Causality Plane as a Complexity Measure for Two-Dimensional Patterns," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-9, August.
    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. Zhang, Boyi & Shang, Pengjian & Zhou, Qin, 2021. "The identification of fractional order systems by multiscale multivariate analysis," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    2. Boaretto, Bruno R.R. & Budzinski, Roberto C. & Rossi, Kalel L. & Masoller, Cristina & Macau, Elbert E.N., 2023. "Spatial permutation entropy distinguishes resting brain states," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    3. Liu, Zhengli & Shang, Pengjian & Wang, Yuanyuan, 2020. "Characterization of time series through information quantifiers," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    4. Wang, Zhuo & Shang, Pengjian, 2021. "Generalized entropy plane based on multiscale weighted multivariate dispersion entropy for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    5. Pessa, Arthur A.B. & Zola, Rafael S. & Perc, Matjaž & Ribeiro, Haroldo V., 2022. "Determining liquid crystal properties with ordinal networks and machine learning," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    6. Carlos F Alvarez & Luis E Palafox & Leocundo Aguilar & Mauricio A Sanchez & Luis G Martinez, 2016. "Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-15, May.
    7. Jauregui, M. & Zunino, L. & Lenzi, E.K. & Mendes, R.S. & Ribeiro, H.V., 2018. "Characterization of time series via Rényi complexity–entropy curves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 498(C), pages 74-85.
    8. Zunino, Luciano & Ribeiro, Haroldo V., 2016. "Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 679-688.

    More about this item

    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:plo:pone00:0117365. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.