2维隐马尔可夫模型的基本问题求解

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;计算机仿真对新算法的实现和运行作了进一步的说明.

Basic Problems Solving for Two-Dimensional Hidden Markov Models

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.