4.6 Article

Temporal infomax leads to almost deterministic dynamical systems

Journal

NEUROCOMPUTING
Volume 52-4, Issue -, Pages 461-466

Publisher

ELSEVIER
DOI: 10.1016/S0925-2312(02)00732-4

Keywords

Markov model; stochastic interaction; information maximization

Ask authors/readers for more resources

The well-known Kullback-Leibler divergence of a random field from its factorization quantifies spatial interdependences of the corresponding stochastic elements. We introduce a generalized measure called 'stochastic interaction' that captures also temporal interdependences. Maximization of stochastic interaction in the setting of Markov chains is shown analytically and by simulations to result in an almost deterministic global dynamics, but almost unpredictable single Unit activity. (C) 2003 Elsevier Science B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available