Diffusion processes on graphs: stochastic differential equations, large deviation principle Page
1 Probab. Theory Relat. Fields 116, 181–220 (2000) cO Springer-Verlag 2000 Mark Freidlin …

Let μ 1 and μ 2 be Borel probability measures on ℝ d with finite moment generating
functions. The main theorem in this paper proves the large deviation principle for a random …

We investigate the validity and accuracy of weak-noise (saddle-point or instanton)
approximations for piecewise-smooth stochastic differential equations (SDEs), taking as an …

In this paper, we are concerned with the numerical approximation of stochastic differential
equations with discontinuous/nondifferentiable drifts. We show that under one-sided …

In this paper, we first prove the strong convergence of the split-step theta methods for non-
autonomous stochastic differential equations under a linear growth condition on the diffusion …

This paper proves the large deviation principle for a class of non-degenerate small noise
diffusions with discontinuous drift and with state-dependent diffusion matrix. The proof is …

This paper concerns the issue of obtaining the large deviation principle for solutions of
stochastic equations with possibly degenerate coefficients. Specifically, we explore the …

We consider a join-the-shortest-queue model, which is as follows. There are K single FIFO
servers and M arrival processes. The customers from a given arrival process can be served …

For the system of $ d $-dim stochastic differential equations, dX^{\varepsilon}(t)= b
(X^{\varepsilon}(t)) dt+\varepsilon dW (t),\quad t\in [0, 1] X^{\varepsilon}(0)= x^ 0\in R^ d …

Pour l'équation differentielle stochastique sur Rd dXε (t)= b (Xε (t)) dt+ εσ (Xε (t)) dW (t), t∈[0,
1], Xε (0)= x0∈ Rd, où b (x) et σ (x) sont lisses à l'exception de l'hyperplan {(x1,..., xd); x1 …