Simulated Anealing Approach for Training Hidden Markov Models
نویسندگان
چکیده
A simulated annealing method for estimating the parameters of Hidden Markov Models is presented. This method is based on the choice of the optimal trajectory of the discrete state. It is applied to both discrete and continuous observations. The program developped needs no speciic initialization of the algorithm by the user, the cooling schedule being general and applicable to any speciic model. The method is applied to data generated randomly and compared to the initial model. Numerical experience in using the method is also presented.
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