Abstract
This paper deals with convergence of the maximum a posterior probability path estimator in hidden Markov models. We show that when the state space of the hidden process is continuous, the optimal path may stabilize in a way which is essentially different from the previously considered finite-state setting.
Original language | English |
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Pages (from-to) | 609-627 |
Number of pages | 19 |
Journal | Bernoulli |
Volume | 17 |
Issue number | 2 |
DOIs | |
State | Published - May 2011 |
Keywords
- Hidden Markov models
- MAP path estimator
- Viterbi algorithm