Hidden Markov Models with Mixed States
نویسنده
چکیده
We note similarities of the state space reconstruction (\Embedology") practiced in numerical work on chaos, state space methods of stochastic systems theory, and the hidden Markov models (HMMs) used in speech research. We review Baum's EM algorithm in general and the speciic forward-backward algorithm that optimizes a class of HMM that has a mixed state space consisting of continuous and discrete parts. We then describe forecasts based on models t to data set D.
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تاریخ انتشار 2007