@article{c9e9c85c3e054a4390d895593d0325f6,
title = "A Robust Estimation of Information Flow in Coupled Nonlinear Systems",
author = "Shivkumar Sabesan and Shivkumar Sabesan and Konstantinos Tsakalis and Andreas Spanias and Leon Iasemidis and Leon Iasemidis",
note = "Part of the Springer Optimization and Its Applications book series (SOIA, volume 38) Transfer entropy (TE) is a recently proposed measure of the information flow between coupled linear or nonlinear systems. In this study, we first suggest improvements in the selection of parameters for the estimation of TE that significantly enhance its accuracy and robustness in identifying the direction and the level of information flow between observed data series generated by coupled complex systems. Second, a new measure, the net transfer of entropy (NTE), is defined based on TE.",
year = "2010",
month = jan,
day = "1",
doi = "10.1007/978-0-387-88630-5\_15",
language = "American English",
journal = "Default journal",
}