Inferring direct directed-information flow from multivariate nonlinear time series

作     者：Michael Jachan Kathrin Henschel Jakob Nawrath Ariane Schad Jens Timmer Björn Schelter 

作者机构：Center for Data Analysis and Modeling (FDM) University of Freiburg Eckerstrasse 1 D-79104 Freiburg Germany Department of Neurology University Hospital of Freiburg Breisacher Strasse 64 D-79098 Freiburg Germany Bernstein Center for Computational Neuroscience (BCCN) University of Freiburg Hansastrasse 9A D-79104 Freiburg Germany Department of Physics University of Freiburg Hermann Herder Strasse 3 D-79104 Freiburg Germany Freiburg Institute for Advanced Studies (FRIAS) University of Freiburg Albertstrasse 19 D-79104 Freiburg Germany 

出 版 物：《Physical Review E》 (物理学评论E辑：统计、非线性和软体物理学)

年 卷 期：2009年第80卷第1期

页      面：011138-011138页

核心收录：

学科分类：07[理学] 070203[理学-原子与分子物理] 0702[理学-物理学] 

基　　金：Seventh Framework Programme  FP7  (211713) 

主　　题：Condensed matter physics 

摘      要：Estimating the functional topology of a network from multivariate observations is an important task in nonlinear dynamics. We introduce the nonparametric partial directed coherence that allows disentanglement of direct and indirect connections and their directions. We illustrate the performance of the nonparametric partial directed coherence by means of a simulation with data from synchronized nonlinear oscillators and apply it to real-world data from a patient suffering from essential tremor.