Bayesian estimation for decision-directed stochastic control

Stochastic processes with a decision-directed control are considered as controlled Markov processes, the state space of which is hybrid; i.e. a product of a discrete set and a Euclidean space. This approach yields a mathematical model for many problems of decision-directed stochastic control. In general, the observations made from the "past" and...

Detection-filter representations for Markov jump diffusions

The problem considered is filtering for Gaussian observations of linear differential systems that are driven by both Wiener processes and marked Poisson point processes. Well-known representations of the MMSE-filter for such a Markov jump-diffusion are a differential for the evolution of its conditional density or differentials for all its...