Information flow within stochastic dynamical systems

Details Information flow within stochastic dynamical systems Information flow within stochastic dynamical systems

2007-10-04

arxiv.org/abs/0710.0913v2

Nonlinear Sciences

Chaotic Dynamics

Revised version, 8 papges, 1 figure

Scientific paper

Information flow or information transfer is an important concept in dynamical systems which has applications in a wide variety of scientific disciplines. In this study, we show that a rigorous formalism can be established in the context of a generic stochastic dynamical system. The resulting measure of of information transfer possesses a property of transfer asymmetry and, when the stochastic perturbation to the receiving component does not rely on the giving component, has a form same as that for the corresponding deterministic system. An application with a two-dimensional system is presented, and the resulting transfers are just as expected. A remarkable observation is that, for two highly correlated time series, there could be no information transfer from one certain series, say $x_2$, to the other ($x_1$). That is to say, the evolution of $x_1$ may have nothing to do with $x_2$, even though $x_1$ and $x_2$ are highly correlated. Information transfer analysis thus extends the traditional notion of correlation analysis by providing a quantitative measure of causality between time series.

Affiliated with

Also associated with

No associations

Rating

Information flow within stochastic dynamical systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Information flow within stochastic dynamical systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Information flow within stochastic dynamical systems will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-563034