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The integrated use of hidden Markov models (HMMs) and Markov chain models can be considered the state-of-the-art for the analysis of sequential data. The former represents a generative model that covers the “appearance” of the underlying data whereas the latter describes restrictions of possible hypotheses sequences. Hidden Markov models describe a two-stage stochastic process with hidden states and...
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