TY - CHAP
T1 - A robust estimation of information flow in coupled nonlinear systems
AU - Sabesan, Shivkumar
AU - Tsakalis, Konstantinos
AU - Spanias, Andreas
AU - Iasemidis, Leon
N1 - Funding Information:
This work was supported in part by NSF (Grant ECS-0601740) and the Science Foundation of Arizona (Competitive Advantage Award CAA 0281-08).
Publisher Copyright:
© Springer Science+Business Media, LLC 2010.
PY - 2010
Y1 - 2010
N2 - 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. Third, we employ surrogate analysis to show the statistical significance of the measures. Fourth, the effect of measurement noise on the measures’ performance is investigated up to S/N = 3 dB. We demonstrate the usefulness of the improved method by analyzing data series from coupled nonlinear chaotic oscillators. Our findings suggest that TE and NTE may play a critical role in elucidating the functional connectivity of complex networks of nonlinear systems.
AB - 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. Third, we employ surrogate analysis to show the statistical significance of the measures. Fourth, the effect of measurement noise on the measures’ performance is investigated up to S/N = 3 dB. We demonstrate the usefulness of the improved method by analyzing data series from coupled nonlinear chaotic oscillators. Our findings suggest that TE and NTE may play a critical role in elucidating the functional connectivity of complex networks of nonlinear systems.
UR - http://www.scopus.com/inward/record.url?scp=84976517790&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84976517790&partnerID=8YFLogxK
U2 - 10.1007/978-0-387-88630-5_15
DO - 10.1007/978-0-387-88630-5_15
M3 - Chapter
AN - SCOPUS:84976517790
T3 - Springer Optimization and Its Applications
SP - 271
EP - 283
BT - Springer Optimization and Its Applications
PB - Springer International Publishing
ER -