HMM training algorithm
2016-08-23
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Hidden Markov models (HM m) traditional training methods of--Baum-W Elch algorithm can only be a local optimum model, thus affecting the
Final recognition rate. CHM m, subparagraph k average method to obtain the original value can solve this problem, but the DHM m improvements are unlikely.
An important feature of evolutionary computation based on global search can be suboptimal solutions, as well as the global optimal solution. This article introduced into evolutionary computation
DHM m in training, and evolution of an improved training method and experimental results indicate that this training approach in its global search and fast convergence
Characteristics of the resulting model is superior to the traditional method and directly derived from evolutionary com
Final recognition rate. CHM m, subparagraph k average method to obtain the original value can solve this problem, but the DHM m improvements are unlikely.
An important feature of evolutionary computation based on global search can be suboptimal solutions, as well as the global optimal solution. This article introduced into evolutionary computation
DHM m in training, and evolution of an improved training method and experimental results indicate that this training approach in its global search and fast convergence
Characteristics of the resulting model is superior to the traditional method and directly derived from evolutionary com
word
算法
hmm
训练
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