Linearized Transfer Entropy for Continuous Second Order Systems
2013
The transfer entropy has proven a useful measure of coupling among components of a dynamical system. This measure effectively captures the influence of one system component on the transition probabilities (dynamics) of another. The original motivation for the measure was to quantify such relationships among signals collected from a nonlinear system. However, we have found the transfer entropy to also be a useful concept in describing linear coupling among system components. In this work we derive the analytical transfer entropy for the response of coupled, second order linear systems driven with a Gaussian random process. The resulting expression is a function of the auto- and cross-correlation functions associated with the system response for different degrees-of-freedom. We show clearly that the interpretation of the transfer entropy as a measure of "information flow" is not always valid. In fact, in certain instances the "flow" can appear to switch directions simply by altering the degree of linear coupling. A safer way to view the transfer entropy is as a measure of the ability of a given system component to predict the dynamics of another.
Keywords:
- Statistics
- Maximum entropy probability distribution
- Mathematical optimization
- Joint entropy
- Generalized relative entropy
- Joint quantum entropy
- Differential entropy
- Mathematics
- Entropy (energy dispersal)
- Entropy (arrow of time)
- Maximum entropy spectral estimation
- Entropy power inequality
- Entropy rate
- Transfer entropy
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
25
References
11
Citations
NaN
KQI