Large deviations for a fractional stochastic heat equation in spatial dimension d, driven by a spatially correlated noise :

Abstract : In this paper we study the Large Deviations Principle (LDP in abbreviation) for a class of Stochastic Partial Differential Equations (SPDEs) in the whole space Rd, with arbitrary dimension d ≥ 1, under random influence which is a Gaussian noise, white in time and correlated in space. The differential operator is a fractional derivative operator. We prove a Large deviations principle for our equation, using a weak convergence approach based on a variational representation of functionals of infinite-dimensional Brownian motion. This approach reduces the proof of LDP to establishing basic qualitative properties for controlled analogues of the original stochastic system.
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Stochastics and Dynamics, World Scientific Publishing, 2016, Vol. 16, No. 1 (2016), 〈10.1142/S0219493716500015〉
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Contributeur : Mohamed Mellouk <>
Soumis le : mardi 17 janvier 2017 - 14:04:18
Dernière modification le : mardi 10 octobre 2017 - 11:22:05

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Mohamed Mellouk, Tarik El Mellali. Large deviations for a fractional stochastic heat equation in spatial dimension d, driven by a spatially correlated noise : . Stochastics and Dynamics, World Scientific Publishing, 2016, Vol. 16, No. 1 (2016), 〈10.1142/S0219493716500015〉. 〈hal-01437848〉

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