CAJ | 학술논문

隐马氏模型作为一种具有双重随机过程的统计模型，具有可靠的概率统计理论基础和强有力的数学结构，已被广泛应用于语音识别、生物序列分析、金融数据分析等领域。由于传统的一阶隐马氏模型无法表示更远状态距离间的依赖关系，就可能会忽略很多有用的统计特征，故有人提出二阶隐马氏模型的概念，但此概念并不严格。本文给出二阶离散隐马尔科夫模型的严格定义，并研究了二阶离散隐马尔科夫模型的两个等价性质。
은마씨모형작위일충구유쌍중수궤과정적통계모형，구유가고적개솔통계이론기출화강유력적수학결구，이피엄범응용우어음식별、생물서렬분석、금융수거분석등영역。유우전통적일계은마씨모형무법표시경원상태거리간적의뢰관계，취가능회홀략흔다유용적통계특정，고유인제출이계은마씨모형적개념，단차개념병불엄격。본문급출이계리산은마이과부모형적엄격정의，병연구료이계리산은마이과부모형적량개등개성질。
Hidden Markov model, as a statistical model of doubly stochastic process, has a reliable theoretical foundation in probability and statistics and strong mathematical structure. It has been widely used in speech recognition, biological sequence analysis, financial data analysis, etc. As the conventional first-order hidden Markov model can not express the dependency relationship between the further distance, many useful statistical characteristic were ignored in many works. Therefore, the concept of second-order hidden Markov model was put forward, but this concept is not strict. In this paper, we give the strict definition of second-order discrete hidden Markov model and study two equivalent properties of the second-order discrete hidden Markov model.