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Open AccessEditorial
Entropy 2014, 16(9), 5068-5077; doi:10.3390/e16095068

Editorial Comment on the Special Issue of “Information in Dynamical Systems and Complex Systems”

Department of Mathematics, Clarkson University, 8 Clarkson Ave, Potsdam, NY 13699-5815, USA
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Received: 22 June 2014 / Accepted: 20 August 2014 / Published: 23 September 2014
(This article belongs to the Special Issue Information in Dynamical Systems and Complex Systems)
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Abstract

This special issue collects contributions from the participants of the “Information in Dynamical Systems and Complex Systems” workshop, which cover a wide range of important problems and new approaches that lie in the intersection of information theory and dynamical systems. The contributions include theoretical characterization and understanding of the different types of information flow and causality in general stochastic processes, inference and identification of coupling structure and parameters of system dynamics, rigorous coarse-grain modeling of network dynamical systems, and exact statistical testing of fundamental information-theoretic quantities such as the mutual information. The collective efforts reported here in reflect a modern perspective of the intimate connection between dynamical systems and information flow, leading to the promise of better understanding and modeling of natural complex systems and better/optimal design of engineering systems. View Full-Text
Keywords: information flow; causality; dynamical systems; modeling; complex systems information flow; causality; dynamical systems; modeling; complex systems
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Bollt, E.M.; Sun, J. Editorial Comment on the Special Issue of “Information in Dynamical Systems and Complex Systems”. Entropy 2014, 16, 5068-5077.

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