隐马尔可夫源和量子随机漫步的可辨识性问题的简单有效解

A. Schönhuth
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引用次数: 3

摘要

基于一种新的随机源代数理论,提出了隐马尔可夫模型可辨识性问题的求解方法。它产生了一个高效实用的算法,可以很容易地实现。现有的方法在隐藏状态的数量上是指数的,因此只适用于有限的程度。该算法同样可以应用于求解量子随机漫步(QRWs)的IP,量子随机漫步最近被作为量子信息理论中的马尔可夫链的类似物提出。此外,该算法可以有效地测试hmm和QRWs的遍历性,这是迄今为止仍然是一个开放的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simple and efficient solution of the identifiability problem for hidden Markov sources and quantum random walks
A solution of the identifiability problem (IP) for hidden Markov models (HMMs), based on a novel algebraic theory for random sources, is presented. It gives rise to an efficient and practical algorithm that can be easily implemented. Extant approaches are exponential in the number of hidden states and therefore only applicable to a limited degree. The algorithm can be equally applied to solve the IP for quantum random walks (QRWs) that have recently been presented as an analogon of Markov chains in quantum information theory. Moreover, the algorithm can be used to efficiently test HMMs and QRWs for ergodicity, which had remained an open problem so far.
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