Literature DB >> 22181382

Effective stochastic behavior in dynamical systems with incomplete information.

Michael A Buice1, Carson C Chow.   

Abstract

Complex systems are generally analytically intractable and difficult to simulate. We introduce a method for deriving an effective stochastic equation for a high-dimensional deterministic dynamical system for which some portion of the configuration is not precisely specified. We use a response function path integral to construct an equivalent distribution for the stochastic dynamics from the distribution of the incomplete information. We apply this method to the Kuramoto model of coupled oscillators to derive an effective stochastic equation for a single oscillator interacting with a bath of oscillators and also outline the procedure for other systems.

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Year:  2011        PMID: 22181382      PMCID: PMC3457716          DOI: 10.1103/PhysRevE.84.051120

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  4 in total

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Authors:  N Brunel; V Hakim
Journal:  Neural Comput       Date:  1999-10-01       Impact factor: 2.026

2.  Kinetic theory of coupled oscillators.

Authors:  Eric J Hildebrand; Michael A Buice; Carson C Chow
Journal:  Phys Rev Lett       Date:  2007-01-31       Impact factor: 9.161

3.  Correlations, fluctuations, and stability of a finite-size network of coupled oscillators.

Authors:  Michael A Buice; Carson C Chow
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2007-09-13

4.  Systematic fluctuation expansion for neural network activity equations.

Authors:  Michael A Buice; Jack D Cowan; Carson C Chow
Journal:  Neural Comput       Date:  2010-02       Impact factor: 2.026

  4 in total
  4 in total

1.  Beyond mean field theory: statistical field theory for neural networks.

Authors:  Michael A Buice; Carson C Chow
Journal:  J Stat Mech       Date:  2013-03       Impact factor: 2.231

2.  Path integral methods for stochastic differential equations.

Authors:  Carson C Chow; Michael A Buice
Journal:  J Math Neurosci       Date:  2015-03-24       Impact factor: 1.300

3.  Dynamic finite size effects in spiking neural networks.

Authors:  Michael A Buice; Carson C Chow
Journal:  PLoS Comput Biol       Date:  2013-01-24       Impact factor: 4.475

4.  Generalized activity equations for spiking neural network dynamics.

Authors:  Michael A Buice; Carson C Chow
Journal:  Front Comput Neurosci       Date:  2013-11-15       Impact factor: 2.380

  4 in total

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