Asymptotic description of stochastic neural networks. II: Characterization of the limit law
From MaRDI portal
Publication:467695
DOI10.1016/j.crma.2014.08.017zbMath1305.92015arXiv1407.2458OpenAlexW2964142701MaRDI QIDQ467695
Olivier Faugeras, James N. Maclaurin
Publication date: 4 November 2014
Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1407.2458
Neural networks for/in biological studies, artificial life and related topics (92B20) Large deviations (60F10)
Related Items (2)
A formalism for evaluating analytically the cross-correlation structure of a firing-rate network model ⋮ Asymptotic description of stochastic neural networks. I: Existence of a large deviation principle
Cites Work
- Asymptotic description of stochastic neural networks. I: Existence of a large deviation principle
- The large deviation principle for hypermixing processes
- Stochastic Neural Field Theory and the System-Size Expansion
- A Master Equation Formalism for Macroscopic Modeling of Asynchronous Irregular Activity States
- Systematic Fluctuation Expansion for Neural Network Activity Equations
This page was built for publication: Asymptotic description of stochastic neural networks. II: Characterization of the limit law
