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Near-Optimality of the Minimum Average Redundancy Code for Almost All Monotone Sources

机译:几乎所有单调信号源的最小平均冗余码的接近最优

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摘要

Consider the source coding problem of finding the optimal code, in the sense of average redundancy, for the class of monotone sources with n symbols. The solution of this problem, known as the M code, is the Huffman code for the average distribution of the monotone sources. In this paper, we evaluate the average redundancy of the M code (on the class of monotone sources), and compare it with that of the Huffman code. It is demonstrated that for large n, although the M code is a fixed code (i.e., the codewords are independent of the symbol probabilities) for all monotone sources, its average redundancy is very close to that of the Huffman code. Moreover, it is shown that when n is large, the M code is a near-optimal code not only in the sense of average redundancy, but also the redundancy of almost all monotone sources. In particular, the redundancy of the M code converges in probability to its average value (= 0.029). As a result, the maximum redundancy of the M code, which can be as large as log n - log In n, rarely occurs.
机译:考虑在平均冗余的意义上针对具有n个符号的单调源类别找到最佳代码的源编码问题。这个问题的解决方案称为M码,它是用于单调信号源平均分布的霍夫曼码。在本文中,我们评估了M码的平均冗余度(在单调源类别上),并将其与霍夫曼码的平均冗余度进行了比较。已经证明,对于大的n,尽管对于所有单调源来说,M码是固定码(即,码字与符号概率无关),但其平均冗余度非常接近于霍夫曼码。此外,示出了当n大时,M码不仅在平均冗余的意义上,而且在几乎所有单调源的冗余的意义上都是接近最佳的代码。尤其是,M代码的冗余概率收敛到其平均值(= 0.029)。结果,很少会发生M代码的最大冗余,该冗余可能与log n-log In n一样大。

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