On the Dynamic Statistical Information Theory
Abstract
We extend present Shannon's static statistical information theory to dynamic processes and establish a dynamic statistical information theory. We derive the nonlinear evolution equations of dynamic information density and dynamic information entropy density. We present the expressions of drift information flow and diffusion information flow, the formulas of information entropy production rate and information dissipation rate. The information dissipation rate is equal to the information entropy production rate in a same dynamic system. Information diffusion and information dissipation occur at the same time. We obtain the dynamic mutual information and dynamic channel capacity reflecting the dynamic dissipation character in the transmission process. These derivations and results are unified and rigorous from evolution equations of dynamic information and dynamic information entropy without adding any extra assumption. Two actual dynamic topics are discussed.
Cite
@article{arxiv.cond-mat/0505009,
title = {On the Dynamic Statistical Information Theory},
author = {Xing Xiu-San},
journal= {arXiv preprint arXiv:cond-mat/0505009},
year = {2007}
}
Comments
27 pages, A Chinese version is published in "Thansanction of Beijing Institute of Technology, 24(1) (2004),1-15"