A General Theory to Estimate Information Transfer in Nonlinear Systems
A General Theory to Estimate Information Transfer in Nonlinear Systems
A general theory for computing information transfers in nonlinear systems driven by deterministic forcings and additive and/or multiplicative noises, is presented. It extends the Liang-Kleeman framework of causality inference based on information transfer across system variables (Liang, 2016. Information flow and causality as rigorous notions ab initio. Phys. Rev. E, …