Recursive identification of HMMs with observations in a finite set
Recursive identification of HMMs with observations in a finite set
复制标题
利用有限集中的观测值递归识别 HMM
DOI：
--
复制
发表时间：
1995
期刊：
影响因子：
--
通讯作者：
L. Mevel
中科院分区：
文献类型：
--
作者：
F. LeGland;L. Mevel
我们考虑基于有限集中的观测来识别部分观测的有限状态马尔可夫链的问题。我们首先研究随着观测值数量增加到无穷大，转移概率的最大似然估计 (MLE) 的渐近行为。特别是，我们展示了相关的对比函数，并讨论了一致性问题。基于这个表达式，我们设计了一种递归识别算法，该算法收敛于对比度函数的局部最小值集合。
We consider the problem of identification of a partially observed finite-state Markov chain, based on observations in a finite set. We first investigate the asymptotic behaviour of the maximum likelihood estimate (MLE) for the transition probabilities, as the number of observations increases to infinity. In particular, we exhibit the associated contrast function, and discuss consistency issues. Based on this expression, we design a recursive identification algorithm, which converges to the set of local minima of the contrast function.