IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v271y1999i3p427-447.html
   My bibliography  Save this article

The use of generalized information dimension in measuring fractal dimension of time series

Author

Listed:
  • Ashkenazy, Y.

Abstract

An algorithm for calculating generalized fractal dimension of a time series using the general information function is presented. The algorithm is based on a strings sort technique and requires O(Nlog2N) computations. A rough estimate for the number of points needed for the fractal dimension calculation is given. The algorithm was tested on analytic example as well as well-known examples, such as, the Lorenz attractor, the Rossler attractor, the van der Pol oscillator, and the Mackey–Glass equation, and compared, successfully, with previous results published in the literature. The computation time for the algorithm suggested in this paper is much less than the computation time according to other methods.

Suggested Citation

  • Ashkenazy, Y., 1999. "The use of generalized information dimension in measuring fractal dimension of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 271(3), pages 427-447.
    • Handle: RePEc:eee:phsmap:v:271:y:1999:i:3:p:427-447
    DOI: 10.1016/S0378-4371(99)00192-2
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437199001922
    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/S0378-4371(99)00192-2?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Antonia Gogoglou & Antonis Sidiropoulos & Dimitrios Katsaros & Yannis Manolopoulos, 2017. "The fractal dimension of a citation curve: quantifying an individual’s scientific output using the geometry of the entire curve," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1751-1774, June.
    2. Dumitru Ciobanu, 2012. "Chaos Tests For Time Series," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 2(40), pages 159-166.
    3. CIOBANU Dumitru & VASILESCU Maria, 2013. "Indications Of Chaotic Behaviour In Usd/Eur Exchange Rate," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 65(6), pages 18-27.

    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:271:y:1999:i:3:p:427-447. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.