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Derivative of the relative entropy over the poisson and Binomial channel

机译:泊松和二项式通道上的相对熵的导数

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In this paper it is found that, regardless of the statistics of the input, the derivative of the relative entropy over the Binomial channel can be seen as the expectation of a function that has as argument the mean of the conditional distribution that models the channel. Based on this relationship we formulate a similar expression for the mutual information concept. In addition to this, using the connection between the Binomial and Poisson distribution we develop similar results for the Poisson channel. Novelty of the results presented here lies on the fact that, expressions obtained can be applied to a wide range of scenarios.
机译:在本文中发现,无论输入的统计信息如何,二项式通道上的相对熵的导数都可以看作是对函数的期望,该函数具有对通道进行建模的条件分布的平均值作为参数。基于这种关系,我们为互信息概念制定了类似的表达方式。除此之外,利用二项式和泊松分布之间的联系,我们为泊松通道得出了相似的结果。这里呈现的结果的新颖性在于这样一个事实,即所获得的表达式可以应用于各种场景。

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