• DocumentCode
    3541430
  • Title

    The relationship between transfer entropy and directed information

  • Author

    Liu, Ying ; Aviyente, Selin

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
  • fYear
    2012
  • fDate
    5-8 Aug. 2012
  • Firstpage
    73
  • Lastpage
    76
  • Abstract
    One challenging problem in the study of complex networks is the quantification of relationships between time series recorded across the network. Two information-theoretic measures, i.e., transfer entropy and directed information, have been extensively studied to capture the causality relationship between subsystems of a network. However, the relationship between these two measures have not been fully investigated to date. In this paper, we derive a formula to show the relationship between these two measures, in particular show that, transfer entropy is equal to the upper bound of directed information rate, and verify it through simulations.
  • Keywords
    entropy; time series; complex networks; directed information; information-theoretic measures; time series; transfer entropy; Entropy; Equations; Information rates; Markov processes; Mathematical model; Mutual information; Upper bound; Causality; Directed information; Transfer entropy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing Workshop (SSP), 2012 IEEE
  • Conference_Location
    Ann Arbor, MI
  • ISSN
    pending
  • Print_ISBN
    978-1-4673-0182-4
  • Electronic_ISBN
    pending
  • Type

    conf

  • DOI
    10.1109/SSP.2012.6319809
  • Filename
    6319809