October 2015
Beginner to intermediate
208 pages
6h 3m
English
Content preview from Hidden Semi-Markov Models
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Preface
A hidden semi-Markov model (HSMM) is a statistical model. In this model, an observation sequence is assumed to be governed by an underlying semi-Markov process with unobserved (hidden) states. Each hidden state has a generally distributed duration, which is associated with the number of observations produced while in the state, and a probability distribution over the possible observations.
Based on this model, the model parameters can be estimated/updated, the predicted, filtered, and smoothed probabilities of partial observation sequence can be determined, goodness of the observation sequence fitting to the model can be evaluated, and the best state sequence of the underlying semi-Markov process can be found.
Due to those capabilities ...
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