A Viterbi smoother for discrete state space model

In this paper we introduce a method for estimating the parameters of a Hidden Markov Model in a discrete time framework, based on new extensions of the Viterbi algorithm. We consider a model in which both the hidden states and observations take values in a finite state space. Recursive estimates are obtained using measure change methods.