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Hypothesis testing for arbitrarily varying source with exponential-type constraint

机译:具有指数型约束的任意变化源的假设检验

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摘要

Hypothesis testing for an arbitrarily varying source (AVS) is considered. We determine the best asymptotic exponent of the probability of error of the second kind when the first kind error probability is less than 2/sup -nr/. This result generalizes the well-known theorem of Hoeffding (1965), Blahut (1974), Csiszar and Longo (1971) for hypothesis testing with an exponential-type constraint. As a corollary in information theory, the best asymptotic error exponent and the r-optimal rate (the minimum compression rate when the error probability is less than 2/sup -nr/, r/spl ges/0) of AVS coding are determined.
机译:考虑对任意变化源(AVS)进行假设检验。当第一类错误概率小于2 / sup -nr /时,我们确定第二类错误概率的最佳渐近指数。该结果推广了Hoeffding(1965),Blahut(1974),Csiszar和Longo(1971)的著名定理,用于带有指数型约束的假设检验。作为信息理论的推论,确定了AVS编码的最佳渐近误差指数和r最优率(误差率小于2 / sup -nr /,r / spl ges / 0时的最小压缩率)。

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