AbstractThe efficient numerical solution of stochastic differential equations is important for applications in many fields. Adaptive schemes, well developed in the deterministic setting, may be one possible way to reduce computational cost. We review the two main step size control algorithms that have been proposed in recent years for stochastic differential systems and compare their efficiency in a simulation study
A difficulty in using Simultaneous Perturbation Stochastics Approximation (SPSA) is its performance ...
. We introduce a variable step size method for the numerical approximation of pathwise solutions to ...
A scheme for stabilizing stochastic approximation iterates by adaptively scaling the step sizes is p...
AbstractThe efficient numerical solution of stochastic differential equations is important for appli...
In this dissertation we obtain an efficient hybrid numerical method for the solution of stochastic d...
AbstractThe numerical solution of stochastic differential equations (SDEs) has been focussed recentl...
The explicit solution of a Stochastic Differential Equation (SDE) can be obtained only when the drif...
The numerical solution of stochastic differential equations (SDEs) has been focused recently on the ...
AbstractWe introduce a variable step size algorithm for the pathwise numerical approximation of solu...
We introduce a variable step size algorithm for the pathwise numerical approximation of solutions to...
AbstractWe propose a new adaptive algorithm with decreasing step-size for stochastic approximations....
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
The stiff stochastic differential equations (SDEs) involve the solution with sharp turning points th...
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
AbstractIn this paper, we will present a new adaptive time stepping algorithm for strong approximati...
A difficulty in using Simultaneous Perturbation Stochastics Approximation (SPSA) is its performance ...
. We introduce a variable step size method for the numerical approximation of pathwise solutions to ...
A scheme for stabilizing stochastic approximation iterates by adaptively scaling the step sizes is p...
AbstractThe efficient numerical solution of stochastic differential equations is important for appli...
In this dissertation we obtain an efficient hybrid numerical method for the solution of stochastic d...
AbstractThe numerical solution of stochastic differential equations (SDEs) has been focussed recentl...
The explicit solution of a Stochastic Differential Equation (SDE) can be obtained only when the drif...
The numerical solution of stochastic differential equations (SDEs) has been focused recently on the ...
AbstractWe introduce a variable step size algorithm for the pathwise numerical approximation of solu...
We introduce a variable step size algorithm for the pathwise numerical approximation of solutions to...
AbstractWe propose a new adaptive algorithm with decreasing step-size for stochastic approximations....
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
The stiff stochastic differential equations (SDEs) involve the solution with sharp turning points th...
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use...
AbstractIn this paper, we will present a new adaptive time stepping algorithm for strong approximati...
A difficulty in using Simultaneous Perturbation Stochastics Approximation (SPSA) is its performance ...
. We introduce a variable step size method for the numerical approximation of pathwise solutions to ...
A scheme for stabilizing stochastic approximation iterates by adaptively scaling the step sizes is p...