论文标题
用于选择指数变量的选择最大估计的正交原理
An Orthogonality Principle for Select-Maximum Estimation of Exponential Variables
论文作者
论文摘要
最近，提议通过k平行通道y1，...，yk编码单方面的指数源x，以使误差标志着x-yi，i = 1，...，...，k，是单面指数且相互独立的x。此外，它显示出最佳的估计器\ hat的最佳估计x的最佳X y siff the Simped sormion sippersion simped simpersion sisteriion，I.Se的最大估计值，即一in。 \ hat {y} = max {y1，...，yk}。在本文中，我们表明，所得估计误差x-\ hat {y}的分布相当于单方面指数源的向后测试通道中最佳噪声的分布，即它是单侧指数分布的，并且统计在统计上独立于关节输出y1，y1，...，...，yk，yk。
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.
