G-convergence of generators and weak convergence of diffusions
General approximation method for the distribution of Markov processes conditioned not to be killed
We consider a strong Markov process with killing and prove an approximation method for the distribution of the process conditioned not to be killed when it is observed. The method is based on a Fleming−Viot type particle system with rebirths, whose particles evolve as independent copies of the original strong Markov process and jump onto each others instead of being killed. Our only assumption is that the number of rebirths of the Fleming−Viot type system doesn’t explode in finite time almost surely...
Generalised transforms, quasi-diffusions, and Désiré André's equation
Generalized Bessel function of type .
Geometric evolution under isotropic stochastic flow.
Grossissement d'une filtration et retournement du temps d'une diffusion