Two traditional parameter estimation algorithms are introduced: the sample training algorithm and the EM algorithm, and then numerical experiments are done to compare with the two algorithms.
介绍了两种传统的参数估计方法:样本训练法和EM算法,并对两种方法进行了数值模拟和对比。
参考来源 - 基于马尔可夫随机场的图像分割研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The speed of the classification is fast without the sample training or pattern matching.
该分类方法避免了样本训练和模板匹配，分类速度快。
This algorithm USES the prediction error threshold to retain the useful information to decrease sample training scale.
该算法利用预测误差阈值进行样本的取舍，在尽量保留有用信息的情况下减小样本训练规模。
Experiments show that this approach performs well in sample training and results in satisfactory verification rate and identification rate.
实验结果表明，文中方法识别具有良好的训练效果，能获得较好的验证率和鉴别率。
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