On Some Distributions and Their Pattern Entropies

G. Shamir
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引用次数: 7

Abstract

We study the block entropy of patterns of sequences generated by uniform and monotonic memoryless source distributions. In the former case, the pattern entropy decreases the most from the memoryless entropy, and in the latter the least. General upper and lower bounds are presented and then applied to these distributions. Tighter bounds are derived for a uniform case. All bounds provide almost precise characterization of the pattern entropies of uniform distributions, distributions over the integers, and the geometric distribution. Of specific interest are distributions over the integers that have infinite entropy rates in the memoryless case but bounded pattern block entropies
关于一些分布及其模式熵
研究了均匀无记忆源分布和单调无记忆源分布产生的序列模式的块熵。在前一种情况下,模式熵比无记忆熵减少最多,而在后一种情况下,模式熵减少最少。给出了一般的上界和下界,然后应用于这些分布。对于统一情况,推导出更严格的边界。所有的边界都提供了均匀分布、整数分布和几何分布的模式熵的几乎精确的表征。特别感兴趣的是在无记忆情况下具有无限熵率但有界模式块熵的整数上的分布
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