Optimal estimation of operator-valued stochastic processes and applications to distributed parameter systems

The paper develops optimal estimation equations for operator-valued discrete-time wide-sense Markov processes. The signals are viewed as linear transformations of wide-sense martingale processes, a general representation which yields relatively simple estimates and error covariances. The infinite-dimensional results are applied to prediction, filtering and smoothing in distributed parameter systems.