This thesis investigates the small time asymptotics of solutions of stochastic equations in infinite dimensions. In this abstract H denotes a separable Hilbert space, A denotes a linear operator on H generating a strongly continuous semigroup and (W(t))t≥0 denotes a separable Hilbert space-valued Wiener process.In chapter 2 we consider the mild solution (Xx(t))t∈[0,1] of a stochastic initial value problemdX = AX dt + dW t ∈ (0, 1]X(0) = x ∈ H ,where the equation has an invariant measure μ. Under some conditions L(Xx(t)) has adensity k(t, x, ·) with respect to μ and we can find the limit limt→0 t ln k(t, x, y). For infinitedimensional H this limit only provides the lower bound of a large deviation prin...
Barbu V, Röckner M. An operatorial approach to stochastic partial differential equations driven by l...
Introduction. The aim of the paper is to establish the convergence of probability laws of solutions ...
AbstractA countable-dimensional stochastic differential equation (*) dX(t) = a(t, X) dt + dW(t) is c...
Let H be a separable Hilbert space. Suppose (Ω, F, Ft, P) is a complete stochastic basis with a righ...
AbstractIn this paper we shall consider the existence, uniqueness, and asymptotic behavior of mild s...
Large deviations theory concerns with the study of precise asymptotics governing the decay rate of p...
We study a reaction-diffusion evolution equation perturbed by a Gaussian noise. Here the leading ope...
We study a reaction-diffusion evolution equation perturbed by a Gaussian noise. Here the leading ope...
This thesis is concerned with stochastic partial differential equations of parabolic type. In the fi...
AbstractWe prove Girsanov-type theorems for Hilbert space-valued stochastic differential equations a...
The aim of this book is to give a systematic and self-contained presentation of the basic results on...
We introduce the Hilbert space-valued Wiener process and the corresponding stochastic integral of It...
AbstractWe consider semilinear stochastic evolution equations driven by a cylindrical Wiener process...
This work consists of four chapters on some aspects of stochastic semilinear evolution equations (SP...
AbstractWe prove a large deviation principle result for solutions of abstract stochastic evolution e...
Barbu V, Röckner M. An operatorial approach to stochastic partial differential equations driven by l...
Introduction. The aim of the paper is to establish the convergence of probability laws of solutions ...
AbstractA countable-dimensional stochastic differential equation (*) dX(t) = a(t, X) dt + dW(t) is c...
Let H be a separable Hilbert space. Suppose (Ω, F, Ft, P) is a complete stochastic basis with a righ...
AbstractIn this paper we shall consider the existence, uniqueness, and asymptotic behavior of mild s...
Large deviations theory concerns with the study of precise asymptotics governing the decay rate of p...
We study a reaction-diffusion evolution equation perturbed by a Gaussian noise. Here the leading ope...
We study a reaction-diffusion evolution equation perturbed by a Gaussian noise. Here the leading ope...
This thesis is concerned with stochastic partial differential equations of parabolic type. In the fi...
AbstractWe prove Girsanov-type theorems for Hilbert space-valued stochastic differential equations a...
The aim of this book is to give a systematic and self-contained presentation of the basic results on...
We introduce the Hilbert space-valued Wiener process and the corresponding stochastic integral of It...
AbstractWe consider semilinear stochastic evolution equations driven by a cylindrical Wiener process...
This work consists of four chapters on some aspects of stochastic semilinear evolution equations (SP...
AbstractWe prove a large deviation principle result for solutions of abstract stochastic evolution e...
Barbu V, Röckner M. An operatorial approach to stochastic partial differential equations driven by l...
Introduction. The aim of the paper is to establish the convergence of probability laws of solutions ...
AbstractA countable-dimensional stochastic differential equation (*) dX(t) = a(t, X) dt + dW(t) is c...