新模型的训练采用最大似然准则，并改进了EM算法来调整模型参数。

The training of the novel model utilizes the maximum likelihood criterion and an effective EM algorithms to adjust model parameters is developed.

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采用最大似然准则的聚类算法其类别接受域为球形或椭球形，可以与模式的分布匹配更好。

Using maximum likelihood criterion in clustering algorithms, the clusters have spherical or ellipsoidal receptive fields and match the distributes of patterns better.

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该方法利用最大似然准则建立目标函数，同时利用非线性共轭梯度法来优化求解目标函数。

The objective function was established based on the maximum likelihood rule, which was solved by nonlinear conjugate gradient method.

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