A convergence condition for optimal nonlinear filtering for systems with unknown parameters

An examination is made of the problem of estimating the state of linear stochastic plant with unknown parameters taking values in a finite set. Stochastic stability theory is used to establish conditions under which the a posteriori probabilities defined on a finite parameter set converge almost surely, both in continuous and discrete time. An example of what happens if the conditions are not satisfied is given.<>