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2维隐马尔可夫模型的基本问题求解

Basic Problems Solving for Two-Dimensional Hidden Markov Models
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摘要 研究了 2维隐马尔可夫模型的三个基本问题 ,包括概率评估问题、最优状态问题和参数估计问题 .通过把 2维隐马尔可夫模型行或者列上的状态序列看作一个马尔可夫模型 ,从理论上分别给出了解决这三个基本问题的新算法 ; The three basic problems of two-dimensional (2-D) hidden Markov models (HMMs) are studied, including probability evaluation, optimal states and parameter estimation. By using the idea that the sequences of states on columns or rows of a 2-D HMM can be seen as states of a 1-D HMM, several new analytic formulae for solving these three problems are theoretically derived and further demonstrated by computer simulation.
作者 李玉鑑
出处 《电子学报》 EI CAS CSCD 北大核心 2004年第11期1833-1838,共6页 Acta Electronica Sinica
基金 北京市教育委员会科技发展计划面上项目 (No .KM2 0 0 31 0 0 0 50 1 3)
关键词 隐马尔可夫模型 状态矩阵 观察矩阵 基本问题求解 Computer simulation Evaluation Mathematical models Matrix algebra Parameter estimation Probability Problem solving Two dimensional
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