| 一种改进的隐马尔可夫模型训练算法 |
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| 引用本文： | 王新民.一种改进的隐马尔可夫模型训练算法[J].孝感学院学报,2004,24(3):74-77. |
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| 作者姓名： | 王新民 |
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| 作者单位： | 孝感学院,物理系,湖北,孝感,432000 |
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| 摘 要： | 将类关联特征(class-dependent feature,CDF)用于隐马尔可夫模型(hidden Markov model,HMM)的建模,提出了一种新的HMM训练算法,与传统的HMM训练算法在理论上完全一致,但新算法避免了直接估计高维的状态输出概率密度函数(probability density function,PDF),可提高模型参数的估计精度.
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| 关 键 词： | 类关联特征 隐马尔可夫模型 训练算法 |
| 文章编号： | 1671-2544(2004)03-0074-04 |
A Modified Training Algorithm of Hidden Markov Model |
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| WANG Xin-min.A Modified Training Algorithm of Hidden Markov Model[J].JOURNAL OF XIAOGAN UNIVERSITY,2004,24(3):74-77. |
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| Authors: | WANG Xin-min |
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| Abstract: | Using the class-dependent feature (CDF) into the modeling problem of hidden Markov model(HMM), this paper presents a novel HMM training algorithm and demonstrates that the new algorithm is the same in theory as traditional algorithm, but without the necessity of estimating high-dimensional probability density function. |
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| Keywords: | class-dependent feature hidden Markov model training algorithm |
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