For a class of stochastic differential equations with reflection for which a certain ${\mathbb{L}}^{p}$ continuity condition holds with p>1, it is shown that any weak solution that is a strong Markov process can be decomposed into the sum of a local martingale and a continuous, adapted process of zero p-variation. When p=2, this implies that the reflected diffusion is a Dirichlet process. Two examples are provided to motivate such a characterization. The first example is a class of multidimensional reflected diffusions in polyhedral conical domains that arise as approximations of certain stochastic networks, and the second example is a family of two-dimensional reflected diffusions in curved domains. In both cases, the reflected diffusions are shown to be Dirichlet processes, but not semimartingales.
@article{1275486188,
author = {Kang, Weining and Ramanan, Kavita},
title = {A Dirichlet process characterization of a class of reflected diffusions},
journal = {Ann. Probab.},
volume = {38},
number = {1},
year = {2010},
pages = { 1062-1105},
language = {en},
url = {http://dml.mathdoc.fr/item/1275486188}
}
Kang, Weining; Ramanan, Kavita. A Dirichlet process characterization of a class of reflected diffusions. Ann. Probab., Tome 38 (2010) no. 1, pp. 1062-1105. http://gdmltest.u-ga.fr/item/1275486188/