Exponential moment bounds and strong convergence rates for tamed-truncated numerical approximations of stochastic convolutions
- Journal Article
In this article we establish exponential moment bounds, moment bounds in fractional order smoothness spaces, a uniform Hölder continuity in time, and strong convergence rates for a class of fully discrete exponential Euler-type numerical approximations of infinite dimensional stochastic convolution processes. The considered approximations involve specific taming and truncation terms and are therefore well suited to be used in the context of SPDEs with non-globally Lipschitz continuous nonlinearities. © Springer Science+Business Media, LLC, part of Springer Nature 2020. Show more
Journal / seriesNumerical algorithms
Pages / Article No.
SubjectStochastic partial differential equation; SPDE; Stochastic convolution; Tamed-truncated numerical approximation; Exponential moment bound; Strong convergence rate
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