Simulated annealing for maximum a Posteriori parameter estimation of hidden Markov models

Abstract

Hidden Markov models are mixture models in which the populations from one observation to the next are selected according to an unobserved finite state-space Markov chain. Given a realization of the observation process, our aim is to estimate both the parameters of the Markov chain and of the mixture model in a Bayesian framework. In this paper, we present… (More)
DOI: 10.1109/18.841176

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