AbstractMild sufficient conditions for exponential ergodicity of a Markov process defined as the solution to a SDE with jump noise are given. These conditions include three principal claims: recurrence condition R, topological irreducibility condition S and non-degeneracy condition N, the latter formulated in terms of a certain random subspace of Rm, associated with the initial equation. Examples are given, showing that, in general, none of the principal claims can be removed without losing ergodicity of the process. The key point in the approach developed in the paper is that the local Doeblin condition can be derived from N and S via the stratification method and a criterium for the convergence in variation of the family of induced measur...
This paper introduces a geometric method for proving ergodicity of degenerate noise driven stochasti...
AbstractThis work is concerned with a class of jump-diffusion processes with state-dependent switchi...
We prove exponential convergence to the invariant measure, in the total variation norm, for solution...
AbstractMild sufficient conditions for exponential ergodicity of a Markov process defined as the sol...
AbstractThe ergodic properties of SDEs, and various time discretizations for SDEs, are studied. The ...
AbstractWe prove exponential convergence to the invariant measure, in the total variation norm, for ...
The ergodic properties of SDEs, and various time discretizations for SDEs, are studied. The ergodici...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
This paper establishes exponential convergence to a unique quasi-stationary distribution in the tota...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
We develop a general framework for studying ergodicity of order-preserving Markov semigroups. We est...
We study the ergodic behaviour of a discrete-time process X which is a Markov chain in a stationary ...
We investigate ergodic properties of the solution of the SDE $dV_t=V_{t-}dU_t+dL_t$, where $(U,L)$ i...
AbstractUnder the conditions of coefficients being non-Lipschitz and the diffusion coefficient being...
This paper introduces a geometric method for proving ergodicity of degenerate noise driven stochasti...
This paper introduces a geometric method for proving ergodicity of degenerate noise driven stochasti...
AbstractThis work is concerned with a class of jump-diffusion processes with state-dependent switchi...
We prove exponential convergence to the invariant measure, in the total variation norm, for solution...
AbstractMild sufficient conditions for exponential ergodicity of a Markov process defined as the sol...
AbstractThe ergodic properties of SDEs, and various time discretizations for SDEs, are studied. The ...
AbstractWe prove exponential convergence to the invariant measure, in the total variation norm, for ...
The ergodic properties of SDEs, and various time discretizations for SDEs, are studied. The ergodici...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
This paper establishes exponential convergence to a unique quasi-stationary distribution in the tota...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
We develop a general framework for studying ergodicity of order-preserving Markov semigroups. We est...
We study the ergodic behaviour of a discrete-time process X which is a Markov chain in a stationary ...
We investigate ergodic properties of the solution of the SDE $dV_t=V_{t-}dU_t+dL_t$, where $(U,L)$ i...
AbstractUnder the conditions of coefficients being non-Lipschitz and the diffusion coefficient being...
This paper introduces a geometric method for proving ergodicity of degenerate noise driven stochasti...
This paper introduces a geometric method for proving ergodicity of degenerate noise driven stochasti...
AbstractThis work is concerned with a class of jump-diffusion processes with state-dependent switchi...
We prove exponential convergence to the invariant measure, in the total variation norm, for solution...