Seminar Details
2016-04-12 (14:00) : Transfer Entropy and Directed Information in Gaussian Diffusion Processes
At Euler building (A002)
Organized by Mathematical Engineering
Speaker :
Nigel J. Newton (University of Essex)
Abstract :
Transfer Entropy and Directed Information are information-theoretic measures of the directional dependency between stochastic processes. They were both originally defined for discrete-time processes: Directed Information in the context of telecommunication systems with feedback, and Transfer Entropy as a means of testing for directional influence in complex systems. The talk will define and evaluate the Transfer Entropy and Directed Information between components of multidimensional Gaussian diffusion processes. When the components are jointly Markov, the natural definitions give rise to measures of influence according to a simple physical principle. More generally, the effect of other components has to be accounted for, and this can be achieved in more than one way. Both quantities can be expressed in terms of the solutions of matrix Riccati equations, and so are easy to compute. Applications to Nonequilibrium Statistical Mechanics will be briefly discussed.