Explicit strong solutions of stochastic differential equations on Hilbert spaces

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Stochastic control of the stochastic partial differential equations (SPDEs) arizing from partial observation control has been studied by Mortensen [M], using a dynamic

Using the method of stochastic characteristics, stochastic flows may be employed to prove uniqueness of solutions of stochastic transport equations under weak regularity hypotheses

To this end, an Itˆ o-Ventzell formula for jump processes is proved and the flow properties of solutions of stochastic differential equations driven by compensated Poisson

The aim of this paper is to study the approximations of stochastic evolu- tion equations of the above type by solutions of stochastic evolution equations driven by pure jump

We develop a white noise framework and the theory of stochastic distribution spaces for Hilbert space valued L´ evy processes in order to study generalized solutions of

We need some concepts and results from Malliavin calculus and the theory of forward in- tegrals to establish explicit representations of strong solutions of forward

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