论文标题
与连续观察的隐藏马尔可夫模型的等效性
Equivalence of Hidden Markov Models with Continuous Observations
论文作者
论文摘要
我们考虑了隐藏的马尔可夫模型，这些模型会散发从连续分布中得出的观测值序列。例如，这样的模型可能会散发出一系列数字，每个数字是从均匀分布中绘制的，但均匀分布的支持取决于隐藏的马尔可夫模型的状态。这样的模型概括了更常见的版本，其中每个观察值是从有限字母中绘制的。我们证明，在多项式时间内可以确定两个具有连续观察的隐藏的马尔可夫模型是否等效。
We consider Hidden Markov Models that emit sequences of observations that are drawn from continuous distributions. For example, such a model may emit a sequence of numbers, each of which is drawn from a uniform distribution, but the support of the uniform distribution depends on the state of the Hidden Markov Model. Such models generalise the more common version where each observation is drawn from a finite alphabet. We prove that one can determine in polynomial time whether two Hidden Markov Models with continuous observations are equivalent.
