  In this paper the relation between nonanticipative rate distortion function
(RDF) and Bayesian filtering theory is investigated using the topology of weak
convergence of probability measures on Polish spaces. The relation is
established via an optimization on the space of conditional distributions of
the so-called directed information subject to fidelity constraints. Existence
of the optimal reproduction distribution of the nonanticipative RDF is shown,
while the optimal nonanticipative reproduction conditional distribution for
stationary processes is derived in closed form. The realization procedure of
nonanticipative RDF which is equivalent to joint-source channel matching for
symbol-by-symbol transmission is described, while an example is introduced to
illustrate the concepts.
