期刊
NEURAL NETWORKS
卷 16, 期 10, 页码 1483-1497出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0893-6080(03)00190-4
关键词
stochastic interactions; Markov chains; entropy; informationn maximization
Spatial interdependences of multiple stochastic units can be suitably quantified by the Kullback-Leibler divergence of the joint probability distribution from the corresponding factorized distribution. In the present paper, a generalized measure for stochastic interaction, which also captures temporal interdependences, is analysed within the setting of Markov chains. The dynamical properties of systems with strongly interacting stochastic units are analytically studied and illustrated by computer simulations. In particular, the emergence of determinism in such systems is demonstrated. (C) 2003 Elsevier Ltd. All rights reserved.
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