In this paper, we address the question of the discretization of stochastic partial differential equations (SPDEs) for excitable media. Working with SPDEs driven by colored noise, we consider a numerical scheme based on finite differences in time (Euler–Maruyama) and finite elements in space. Motivated by biological considerations, we study numerically the emergence of reentrant patterns in excitable systems such as the Barkley or Mitchell–Schaeffer models
Abstract. We study finite element approximations of stochastic partial dif-ferential equations of Gi...
Abstract. We study stochastic partial differential equations (SPDEs) driven by space-time white nois...
Abstract. We consider the numerical approximation of a general second order semi–linear parabolic st...
International audienceIn this paper, we address the question of the discretization of Stochastic Par...
We discuss the numerical solution of a number of stochastic perturbations of the Barkley model of ex...
AbstractWe discuss the numerical solution of a number of stochastic perturbations of the Barkley mod...
These notes describe numerical issues that may arise when implementing a simulation method for a sto...
We present a method for mesoscopic, dynamic Monte Carlo simulations of pattern formation in excitabl...
A stochastic partial differential equation (SPDE) is a partial differential equation containing a ra...
We present a method for mesoscopic, dynamic Monte Carlo simulations of pattern formation in excitabl...
A stochastic cellular automaton is developed for modeling waves in excitable media. A scale of key f...
In this thesis, we consider four different stochastic partial differential equations. Firstly, we st...
Constructing discrete models of stochastic partial differential equations is very delicate. I apply ...
We review the behavior of theoretical models of excitable systems driven by Gaussian white noise. We...
Pattern formation has been widely observed in extended chemical and biological processes. Although t...
Abstract. We study finite element approximations of stochastic partial dif-ferential equations of Gi...
Abstract. We study stochastic partial differential equations (SPDEs) driven by space-time white nois...
Abstract. We consider the numerical approximation of a general second order semi–linear parabolic st...
International audienceIn this paper, we address the question of the discretization of Stochastic Par...
We discuss the numerical solution of a number of stochastic perturbations of the Barkley model of ex...
AbstractWe discuss the numerical solution of a number of stochastic perturbations of the Barkley mod...
These notes describe numerical issues that may arise when implementing a simulation method for a sto...
We present a method for mesoscopic, dynamic Monte Carlo simulations of pattern formation in excitabl...
A stochastic partial differential equation (SPDE) is a partial differential equation containing a ra...
We present a method for mesoscopic, dynamic Monte Carlo simulations of pattern formation in excitabl...
A stochastic cellular automaton is developed for modeling waves in excitable media. A scale of key f...
In this thesis, we consider four different stochastic partial differential equations. Firstly, we st...
Constructing discrete models of stochastic partial differential equations is very delicate. I apply ...
We review the behavior of theoretical models of excitable systems driven by Gaussian white noise. We...
Pattern formation has been widely observed in extended chemical and biological processes. Although t...
Abstract. We study finite element approximations of stochastic partial dif-ferential equations of Gi...
Abstract. We study stochastic partial differential equations (SPDEs) driven by space-time white nois...
Abstract. We consider the numerical approximation of a general second order semi–linear parabolic st...