Entropy Computation in Partially Observed Markov Chains
François Desbouvries · AIP conference proceedings · 2006
Abstract. Let X = {Xn}n∈IN be a hidden process and Y = {Yn}n∈IN be an observed process. We assume that (X,Y) is a (pairwise) Markov Chain (PMC). PMC are more general than Hidden Markov Chains (HMC) and yet enable the development of efficient parameter estimation and Bayesian restoration algorithms. In this paper we propose a fast (i.e., O(N)) algorithm for computing the entropy of {Xn} N n=0 given an observation sequence {yn} N n=0.