We consider a numerical approximation of a linear quadratic control problem constrained by the stochastic heat equation with nonhomogeneous Neumann boundary conditions. This involves a combination of distributed and boundary control, as well as both distributed and boundary noise. We apply the finite element method for the spatial discretization and the linear implicit Euler method for the temporal discretization. Due to the low regularity induced by the boundary noise, convergence orders above 1/2 in space and 1/4 in time cannot be expected. We prove such optimal convergence orders for our full discretization when the distributed noise and the initial condition are sufficiently smooth. Under less smooth conditions the convergence order is ...
International audienceWe present here the discretization by a finite-volume scheme of a heat equatio...
We prove that the implicit time Euler scheme coupled with finite elements space discretization for t...
In this thesis we study mathematically and computationally optimal control problems for stochastic e...
We verify strong rates of convergence for a time-implicit, finite-element based space-time discretiz...
The stochastic heat equation driven by additive noise is discretized in the spatial variables by a s...
A finite element Galerkin spatial discretization together with a backward Euler scheme is implemente...
Abstract. We consider the numerical approximation of a general second order semi–linear parabolic st...
We find the weak rate of convergence of the spatially semidiscrete finite element approximation of t...
Abstract. We study algorithms for approximation of the mild solution of stochastic heat equations on...
AbstractIn this paper we study mathematically and computationally optimal control problems for stoch...
We study the finite element method for stochastic parabolic partial differential equations driven by...
Mukam JD, Tambue A. Strong convergence of the linear implicit Euler method for the finite element di...
We are concerned with the optimal control of a nonlinear stochastic heat equation on a bounded real ...
In this paper the numerical solution of nonautonomous semilinear stochastic evolution equations driv...
In this thesis, we give a mathematical background of solving a linear quadratic control problem for ...
International audienceWe present here the discretization by a finite-volume scheme of a heat equatio...
We prove that the implicit time Euler scheme coupled with finite elements space discretization for t...
In this thesis we study mathematically and computationally optimal control problems for stochastic e...
We verify strong rates of convergence for a time-implicit, finite-element based space-time discretiz...
The stochastic heat equation driven by additive noise is discretized in the spatial variables by a s...
A finite element Galerkin spatial discretization together with a backward Euler scheme is implemente...
Abstract. We consider the numerical approximation of a general second order semi–linear parabolic st...
We find the weak rate of convergence of the spatially semidiscrete finite element approximation of t...
Abstract. We study algorithms for approximation of the mild solution of stochastic heat equations on...
AbstractIn this paper we study mathematically and computationally optimal control problems for stoch...
We study the finite element method for stochastic parabolic partial differential equations driven by...
Mukam JD, Tambue A. Strong convergence of the linear implicit Euler method for the finite element di...
We are concerned with the optimal control of a nonlinear stochastic heat equation on a bounded real ...
In this paper the numerical solution of nonautonomous semilinear stochastic evolution equations driv...
In this thesis, we give a mathematical background of solving a linear quadratic control problem for ...
International audienceWe present here the discretization by a finite-volume scheme of a heat equatio...
We prove that the implicit time Euler scheme coupled with finite elements space discretization for t...
In this thesis we study mathematically and computationally optimal control problems for stochastic e...