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On the optimal asymptotic performance of universal ordering and of discrimination of individual sequences

机译:关于普遍排序和个体序列的判别的最佳渐近性能

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摘要

The authors consider the problem of ordering strings of a fixed length over a discrete alphabet according to decreasing probabilities of having been emitted by an unknown finite-state source. Data compression is applied to derive a universal algorithm that solves this problem with an optimal asymptotic performance. This result is employed in the solution of the following problem: discriminate an individual sequence as emitted by an independently identically distributed random source of equally likely symbols or as a signal corrupted by noise. Tight lower and upper bounds on the asymptotic performance of finite-state discriminators are given.
机译:作者考虑到根据未知有限状态源发出的概率降低而在离散字母上按固定长度排序字符串的问题。应用数据压缩来导出通用算法,该算法以最佳渐近性能解决此问题。该结果用于以下问题的解决方案:区分单个序列,该序列是由具有相同可能性的符号的独立均匀分布的随机源发出的,或者是被噪声破坏的信号。给出了有限状态鉴别器渐近性能的上下界。

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