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
Link To Document