【Abstract】A control systems problem addressed several decades ago was to determine from measurements on different parts of a system whether there was feedback present in the system or not. Such problems as it turned out were of very great interest to economists, who studied this sort of question intensively. The name of Nobel prize-winning economist, Clive Granger, is part of the term Granger Causality, which is a cohesive body of ideas in stochastic processes, relevant to treating the question. More recently, such questions have arisen in theoretical and experimental studies in functional neuroimaging, which can attempt to find directional pathways in the brain.
This talk introduces a number of examples of causality and then reviews the definition of Granger causality and several characterizations of it. Granger causality is related to, but not identical with, physical causality. Then recent joint work with M Deistler and J.-M. Dufour is reviewed, examining the effect of measurement noise, measurement filtering and subsampling of measured signals on conclusions of a Granger causality nature.
【Brief CV】Brian D. O Anderson obtained his PhD in electrical engineering from Stanford University, and subsequently held positions at Stanford, University of Newcastle and Australian National University and Hangzhou Dianzi University. He is a Fellow of the Australian Academy of Science, the Australian Academy of Technological Sciences and Engineering, the Royal Society, and a Foreign Member of the US National Academy of Engineering. He was President of the International Federation of Automatic Control from 1990 to 1993, having served earlier in various IFAC roles, including Editor of Automatica. He was President of the Australian Academy of Science from 1998 to 2002. His current research interests are in distributed control, sensor networks and econometric modelling.