MEAN 1ST-PASSAGE TIME FOR SYSTEMS DRIVEN BY PRE-GAUSSIAN NOISE - NATURAL BOUNDARY-CONDITIONS

In order to determine the mean first-passage time for systems driven b y a superposition of suitably scaled independent dichotomous Markovian processes (pre-Gaussian noise), the well-known absorbing boundary con ditions must be complemented in the generic case by a novel type of na tural boundary conditions. We treat explicitly a linear stochastic flo w for the superposition of up to five dichotomous processes and compar e the analytic results with a digital simulation for these processes a nd an Ornstein-Uhlenbeck process.