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Nonparametric entropy estimation for stationary processes and random fields, with applications to English text

机译:平稳过程和随机场的非参数熵估计及其在英文文本中的应用

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摘要

We discuss a family of estimators for the entropy rate of a stationary ergodic process and prove their pointwise and mean consistency under a Doeblin-type mixing condition. The estimators are Cesaro averages of longest match-lengths, and their consistency follows from a generalized ergodic theorem due to Maker (1940). We provide examples of their performance on English text, and we generalize our results to countable alphabet processes and to random fields.
机译:我们讨论了平稳的遍历过程的熵速率的估计量族,并证明了它们在Doeblin型混合条件下的逐点和均值一致性。估计量是最长匹配长度的Cesaro平均值,其一致性来自Maker(1940)提出的广义遍历定理。我们提供了其在英语文本上的性能示例,并将结果概括为可数的字母过程和随机字段。

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