指数变量选择最大值估计的一个随机性原理
An Orthogonality Principle for Select-Maximum Estimation of Exponential Variables
摘要：
最近提出了经由K个并行通道Y1，...，.. K，是单侧指数的，并且在给定X的情况下相互独立。此外，它表明，源X的最佳估计量\hat{Y}相对于单侧误差准则，简单地由输出的最大值给出，即，\hat{Y} = max{Y1，.，YK}。本文证明了所得估计误差X - \hat{Y}的分布等价于单侧指数源的反向测试通道中的最佳噪声的分布，即，它是单侧指数分布的，并且在统计上独立于联合输出Y1，...，好的
英文摘要：
It was recently proposed to encode the one-sided exponential source X via K parallel channels, Y1, ..., YK , such that the error signals X - Yi, i = 1,...,K, are one-sided exponential and mutually independent given X. Moreover, it was shown that the optimal estimator \hat{Y} of the source X with respect to the one-sided error criterion, is simply given by the maximum of the outputs, i.e., \hat{Y} = max{Y1,..., YK}. In this paper, we show that the distribution of the resulting estimation error X - \hat{Y} , is equivalent to that of the optimum noise in the backward test-channel of the one-sided exponential source, i.e., it is one-sided exponentially distributed and statistically independent of the joint output Y1,...,YK.
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