Maximum a Posteriori Estimation of Coupled Hidden Markov Models
نویسندگان
چکیده
Coupled Hidden Markov Models (CHMM) are a tool which model interactions between variables in state space rather than observation space. Thus they may reveal coupling in cases where classical tools such as correlation fail. In this paper we derive the maximum a posteriori equations for the Expectation Maximization algorithm. The use of the models is demonstrated on simulated data, as well as in biomedical signal analysis.
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عنوان ژورنال:
- VLSI Signal Processing
دوره 32 شماره
صفحات -
تاریخ انتشار 2002