IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v388y2009i22p4703-4712.html
   My bibliography  Save this article

Nonlinear non-extensive approach for identification of structured information

Author

Listed:
  • Rebollo-Neira, Laura
  • Plastino, A.

Abstract

The problem of separating structured information representing phenomena of differing natures is considered. A structure is assumed to be independent of the others if can be represented in a complementary subspace. When the concomitant subspaces are well separated the problem is readily solvable by a linear technique. Otherwise, the linear approach fails to correctly discriminate the required information. Hence, a non-extensive approach is proposed. The resulting nonlinear technique is shown to be suitable for dealing with cases that cannot be tackled by the linear one.

Suggested Citation

  • Rebollo-Neira, Laura & Plastino, A., 2009. "Nonlinear non-extensive approach for identification of structured information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(22), pages 4703-4712.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:22:p:4703-4712
    DOI: 10.1016/j.physa.2009.08.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437109006128
    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.2009.08.003?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. Neira, L.Rebollo & Constantinides, A.G. & Plastino, A. & Zyserman, F. & Alvarez, A. & Bonetto, R. & Viturro, H., 1993. "Statistical inference, state distribution, and noisy data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 198(3), pages 514-537.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Xu, Zhiqiang & Rebollo-Neira, Laura & Plastino, A., 2010. "Subspace modelling for structured noise suppression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2030-2035.

    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.

      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:388:y:2009:i:22:p:4703-4712. 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.