Measuring Information Transfer
Thomas Schreiber
Abstract
An information theoretic measure is derived that quantifies the statistical coherence between systems evolving in time. The standard time delayed mutual information fails to distinguish information that is actually exchanged from shared information due to common history and input signals. In our new approach, these influences are excluded by appropriate conditioning of transition probabilities. The resulting transfer entropy is able to distinguish driving and responding elements and to detect asymmetry in the coupling of subsystems.
Create a lesson
Related papers
A Second-Order Asymptotic Expansion for Nonlinear Filtering in the Lorenz--63 System
Masahiro Kurisaki, Kota Takeda
Heterogeneity-induced chaos in globally coupled Stuart--Landau oscillators
Luekai Zhao, Nariya Uchida
Adiabatic confinement and escape in an open billiard
Matheus Rolim Sales, Leonardo Costa de Souza, Ricardo Luiz Viana et al.
A Renormalization-Group Hierarchy of Stochastic Effective Dynamics Learned through Path Integrals
Yuki Yasuda, Tobias Bischoff
ETM-3D: A One-Parameter Multistable Quadratic Flow with an Explicit Absorbing Set and Intermittent Chaos
Roya Khalili-Amirabadi, Mohsen Jalaeian-Farimani
Influence of astrocyte feedback and noise on breathing neural clusters
Ediline L. F. Nguessap, Thierry Njougouo, Fernando F. Ferreira