有限混合和隐马尔可夫模型状态估计的比较

I. Nagy, E. Suzdaleva, T. Mlynarova
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引用次数: 0

摘要

针对动态切换系统的状态估计问题,提出了许多不同的算法。选择最合适的并不是一件简单的事。本文讨论了两种著名的状态估计的检验方法:有限混合递归估计和隐马尔可夫模型迭代法。对这些在线和离线对应物的比较的讨论是真正有趣的。本文通过实验对这些方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of state estimation using finite mixtures and hidden Markov models
Many various algorithms are developed for state estimation of dynamic switching systems. It is not a straightforward task to choose the most suitable one. This paper deals with testing of state estimation via two well-known approaches: recursive estimation with finite mixtures and iterative technique with hidden Markov models. A discussion of comparison of these online and offline counterparts is of true interest. The paper describes experiments providing a comparison of these methods.
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