IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v286y2000i3p457-473.html
   My bibliography  Save this article

Relative complexity changes in time series using information measures

Author

Listed:
  • Torres, M.E.
  • Gamero, L.G.

Abstract

Estimation of complexity is of great interest in nonlinear signal and system analysis. Several complexity measures have been proposed: Lyapunov exponents, Lempel and Ziv, approximate entropy. In the present study, complexity measures derived from Shannon entropy, Harvda–Charvat–Daróvczy–Tsallis (q-entropies) and their corresponding relative information measures are presented and evaluated in the context of nonlinear systems presenting abrupt complexity changes. The performance of the proposed measures in the presence of controlled complexity is evaluated through numerical experiments using nonlinear models. An example with heart rate variability signals is presented. The results obtained show that the entropic and the relative complexity measures approach allow to discern complexity changes in a similar qualitative way compared against classical techniques but with much less computational cost and less amount of data. In the presence of noise, the relative complexity measures behave as robust tools for relative complexity changes detection. Time-scale complexity analyses are presented using the continuous multiresolution entropies. The assessment of time-scale complexity changes is also discussed.

Suggested Citation

  • Torres, M.E. & Gamero, L.G., 2000. "Relative complexity changes in time series using information measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 286(3), pages 457-473.
    • Handle: RePEc:eee:phsmap:v:286:y:2000:i:3:p:457-473
    DOI: 10.1016/S0378-4371(00)00309-5
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437100003095
    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(00)00309-5?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. Zozor, S. & Ravier, P. & Buttelli, O., 2005. "On Lempel–Ziv complexity for multidimensional data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 345(1), pages 285-302.
    2. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    3. Dingle, Kamaludin & Kamal, Rafiq & Hamzi, Boumediene, 2023. "A note on a priori forecasting and simplicity bias in time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    4. Torres, H.M. & Gurlekian, J.A. & Rufiner, H.L. & Torres, M.E., 2006. "Self-organizing map clustering based on continuous multiresolution entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(1), pages 337-354.
    5. Lovallo, Michele & Lapenna, Vincenzo & Telesca, Luciano, 2005. "Transition matrix analysis of earthquake magnitude sequences," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 33-43.
    6. Sivadasan, S. & Efstathiou, J. & Calinescu, A. & Huatuco, L. Huaccho, 2006. "Advances on measuring the operational complexity of supplier-customer systems," European Journal of Operational Research, Elsevier, vol. 171(1), pages 208-226, May.

    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:286:y:2000:i:3:p:457-473. 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.