1. A signal processing system for generating a probability distribution indicative of the current underlying value of a time-varying source, said system comprising: state change probability matrix means defining the probabilities of all possible state-to-state changes in a source capable of assuming any of a finite number of states, wherein said probability matrix means provides as an output a set of probabilities relating to the current source state, derived from a corresponding set of probabilities relating to the effect of noise on a related observed signal at present and prior sample times; noise model means for generating a set of probabilities that an observed value of the time-varying signal would have occurred if the underlying value of the source were in each of its possible states; and means for combining the set of probabilities generated by said probability matrix means with the set of probabilities generated by said noise model means, to yield the desired probability distribution, which is then fed back to said probability matrix means for generation of a set of probabilities with respect to the next sample time.