单调分布和m-模态分布的有效压缩

2014 IEEE International Symposium on Information Theory Pub Date : 2014-08-11 DOI:10.1109/ISIT.2014.6875157

Jayadev Acharya, Ashkan Jafarpour, A. Orlitsky, A. Suresh

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引用次数: 7

摘要

我们考虑根据k个元素的单调或m-模态分布独立绘制的n个样本的通用压缩。我们表明，对于所有这些分布，如果k = exp(o(n/log n))，则每个样本的冗余减小到0，如果k = exp(Ω(n))，则至少是一个常数。

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Efficient compression of monotone and m-modal distributions

We consider universal compression of n samples drawn independently according to a monotone or m-modal distribution over k elements. We show that for all these distributions, the per-sample redundancy diminishes to 0 if k = exp(o(n/log n)) and is at least a constant if k = exp(Ω(n)).

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2014 IEEE International Symposium on Information Theory

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