Large Deviations for Nonlocal Stochastic Neural Fields

We study the effect of additive noise on integro-differential neural field equations. In particular, we analyze an Amari-type model driven by a \(Q\)-Wiener process and focus on noise-induced transitions and escape. We argue that proving a sharp Kramers' law for neural fields poses substanial d...

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Veröffentlicht in:	arXiv.org 2013-09
Hauptverfasser:	Kuehn, Christian, Riedler, Martin G
Format:	Artikel
Sprache:	eng
Schlagworte:	Galerkin method Mathematics - Dynamical Systems Mathematics - Probability Noise Partial differential equations Physics - Biological Physics Quantitative Biology - Neurons and Cognition
Online-Zugang:	Volltext
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