Abstract

A class of complex self-organizing systems subjected to fluctuations of environmental or intrinsic origin and to nonequilibrium constraints in the form of an external periodic forcing is analyzed from the standpoint of information theory. Conditions under which the response of information entropy and related quantities to the nonequilibrium constraint can be optimized via a stochastic resonance-type mechanism are identified, and the role of key parameters is assessed.

Highlights

  • One of the principal features of complex self-organizing systems is the multitude of a priori available states [1]

  • We explore this connection in a class of multistable systems subjected to stochastic variability generated by fluctuations of intrinsic or environmental origin, as well as to a systematic nonequilibrium constraint in the form of a weak external periodic forcing

  • A nonlinear system subjected to a nonequilibrium constraint in the form of a periodic forcing, giving rise to complex behavior in the form of fluctuation-induced transitions between multiple steady states and of stochastic resonance, was considered

Read more

Summary

Introduction

One of the principal features of complex self-organizing systems is the multitude of a priori available states [1]. We focus on the linear response, which will provide us with both qualitative and quantitative insights into the role of the principal parameters involved in the problem This induces a decomposition of the transfer operator T and of the probability vector p = ( p1 , · · · , pn ) T in Equation (5) in the form:. We notice the bilinear structure of σI in which the factors within the sum can be viewed as generalized (probability) fluxes and their associated generalized forces This is reminiscent of the expression of entropy production of classical irreversible thermodynamics [10]. The presence of the forcing will change this situation radically by inducing non-trivial correlations and information exchanges within the system

Nonequilibrium Dynamics of Information and Stochastic Resonance
Information Entropy and Redundancy
Information Entropy Production
Information Transfer and Kolmogorov–Sinai Entropy
Conclusions
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.