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Abstract: In a hidden Markov model (HMM) the underlying nite-state Markov chain cannot be observed directly but only by an additional process. We are interested in estimating the unknown path of the Markov chain. The most widely used estimator is the maximum a posteriori path estimator (MAP path estimator). It can be calculated e ectively by the Viterbi algorithm as is, e.g., frequently done in the eld of coding theory, correction of intersymbol interference and speech recognition. We investigate... (Update)
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BibTeX entry: (Update)
@misc{ caliebe-convergence,
author = "Amke Caliebe and Uwe Rösler",
title = "Convergence of the Maximum a Posteriori Path Estimator in Hidden Markov
Models",
url = "citeseer.ist.psu.edu/caliebe02convergence.html" }
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