Estimation of Hybrid HMM/MLP models
نویسنده
چکیده
Hybrid HMM/MLP models are useful to model piecewise stationary non-linear time series. A popular way to estimate the parameters of such models is to use the E.M. algorithm thanks to the Baum and Welch, forward-backward, algorithm. In this paper, we study a convenient way to estimate the parameters thanks to differential optimization. This new method can dramatically improve the time of calculus for long time series.
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