A Bayesian approach to problems in stochastic estimation and control

摘要: In this paper, a general class of stochastic estimation and control problems is formulated from the Bayesian Decision-Theoretic viewpoint. A discussion as to how these can be solved step by in principle practice approach presented. As specific example, closed form Wiener-Kalman solution for linear Gaussian noise derived. The purpose paper show that provides; 1) unifying framework within which pursue further researches problems, 2) necessary computations difficulties must overcome problems. An example nonlinear, non-Gaussian problem also solved.