Spatio-temporal hybrid (PDMP) models: central limit theorem and Langevin approximation for global fluctuations. Application to electrophysiology

DOI10.3150/13-BEJ583zbMath1327.60063arXiv1304.5651OpenAlexW2004613433MaRDI QIDQ2348722

Michèle Thieullen, Martin Georg Riedler

Publication date: 15 June 2015

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1304.5651

zbMATH Keywords

law of large numberscentral limit theoremneurosciencepiecewise deterministic Markov processstochastic PDEglobal fluctuations

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05) Continuous-time Markov processes on general state spaces (60J25) Neural biology (92C20) Strong limit theorems (60F15) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) Functional limit theorems; invariance principles (60F17)

Related Items (3)

Spatio-temporal averaging for a class of hybrid systems and application to conductance-based neuron models ⋮ A multiscale stochastic criminal behavior model and the convergence to a piecewise-deterministic-Markov-process limit ⋮ Change-point detection for piecewise deterministic Markov processes

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