Category: seminar “Malliavin calculus”

Speaker: Xia Chen (University of Tennessee, Knoxville) Title: Intermittency for hyperbolic Anderson models with time-independent Gaussian noise Abstract. Intuitively, inttermittency refers to a state of the system with random noise in which the high peak is rare but real. In mathematics, it can be described in terms of moment asymptotics of the system. Compared to the parabolic Anderson equation, […]

Speaker: Mykola Portenko (Institute of Mathematics, NAS of Ukraine) Topic: Brownian motion in a Euclidean space with a membrane located on a given hyperplane. The presentation is based on the results of joint investigations with Prof. Bohdan Kopytko. Abstract. Brownian motion in a Euclidean space with a membrane located on a given hyperplane and acting in a […]

Speaker: Andrey Dorogovtsev (Institute of Mathematics, NAS of Ukraine) Topic: Isonormal processes associated with Brownian motion

Speaker: Mykola Vovchanskyi (Institute of Mathematics, NAS of Ukraine) Topic: On the convergence of 1-point densities for Arratia flows

Speaker: Mikhail Neklyudov Topic: Ergodicity for infinite particle systems with locally conserved quantities

Speaker: Naoufel Salhi (University of Carthage) Topic: Intermittency in the Itô-Wiener expansion of the self-intersection local times of the Brownian motion

Speaker: Andrey Pilipenko (Institute of Mathematics, NAS of Ukraine) Topic: On a skew Lévy process

Speaker: Mariia Belozerowa (Odessa I.I. Mechnikov National University) Title: Lyapunov exponents of the system of stochastic differential equations with interaction

Speaker: Nasir Ganikhodzhaev (V.I.Romanovsky Institute of Mathematics) Title: Quadratic Stochastic Operators and Inhomogeneous Markov Chains

Speaker: Alexander Veretennikov (Institute for Information Transmission Problems (Kharkevich Institute)) Topic: On recurrence of diffusion with switching Abstract. The Markov system “Diffusion with switching” is otherwise called “Diffusion in a random environment”, where this environment is due to a discrete component of the system, which is usually an independent ergodic Markov chain. Assume that depending on this discrete […]