We consider the Sequential Probability Ratio Test applied to Hidden Markov Models. Given two Hidden Markov Models and a sequence of observations generated by one of them, the Sequential Probability Ratio Test attempts to decide which model produced the sequence. We show relationships between the execution time of such an algorithm and Lyapunov exponents of random matrix systems. Further, we give complexity results about the execution time taken by the Sequential Probability Ratio Test.

翻译：我们认为对隐藏的 Markov 模型应用了序列概率测试。 鉴于两个隐藏的 Markov 模型和其中之一产生的一系列观测, 序列概率测试试图决定哪个模型生成序列。 我们显示了这种算法的执行时间与随机矩阵系统的 Lyapunov 演示数据之间的关系。 此外, 我们给出了序列概率测试的执行时间的复杂结果 。