A variational approach to nonlinear stochastic differential equations with linear multiplicative noise
ESAIM: Control, Optimisation and Calculus of Variations, Tome 25 (2019), article no. 71.

One introduces a new concept of generalized solution for nonlinear infinite dimensional stochastic differential equations of subgradient type driven by linear multiplicative Wiener processes. This is defined as solution of a stochastic convex optimization problem derived from the Brezis-Ekeland variational principle. Under specific conditions on nonlinearity, one proves the existence and uniqueness of a variational solution which is also a strong solution in some significant situations. Applications to the existence of stochastic total variational flow and to stochastic parabolic equations with mild nonlinearity are given.

Reçu le :
Accepté le :
DOI : 10.1051/cocv/2018065
Classification : 60H15, 47H05, 47J05
Mots-clés : Wiener process, convex function, subdifferential, stochastic total variation flow
Barbu, Viorel 1

1
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Barbu, Viorel. A variational approach to nonlinear stochastic differential equations with linear multiplicative noise. ESAIM: Control, Optimisation and Calculus of Variations, Tome 25 (2019), article no. 71. doi : 10.1051/cocv/2018065. http://www.numdam.org/articles/10.1051/cocv/2018065/

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