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Tsallis differential entropy and divergences derived from the generalized Shannon-Khinchin axioms

机译:Tsallis差异熵和来自广义的Shannon-Khinchin公理的分歧

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In discrete systems, Shannon entropy is well known to be characterized by the Shannon-Khinchin axioms. Recently, this set of axioms was generalized for Tsallis entropy, one-parameter generalization of Shannon entropy. In continuous systems, Shannon differential entropy has been introduced as a natural extension of the above Shannon entropy without using an axiomatic approach. We derive the generalized entropy function as a solution of the functional equation determined by the generalized Shannon additivity, one of the most important axiom of the generalized Shannon-Khinchin axioms for Tsallis entropy. This generalized entropy function naturally introduces Tsallis differential entropy and two Tsallis divergences. In particular, one (Csiszaacuter type) of the divergences has almost the same form as the alpha-divergence in information geometry and the other the Bregman type divergence. Our results reveal that the generalized Shannon additivity representing a branch structure of a rooted tree plays an essential role in the determination of these entropies.
机译:在离散系统,香农熵是公知的由香农 - 欣钦公理来表征。近日,这组公理被概括为Tsallis熵,香农熵的单参数推广。在连续系统中,香农熵差已经被引入作为上述信息熵的自然延伸,而无需使用一个公理的方法。我们推导出广义熵函数由广义加香,广义香农 - 欣钦公理Tsallis熵的最重要的公理的一个确定的函数方程的解。此广义熵函数自然介绍Tsallis微分熵和两个Tsallis分歧。具体地,分歧中的一个(Csiszaacuter型)具有几乎相同的形式在信息几何所述α-发散和另一个布莱格曼散度类型。我们的研究结果显示,代表有根树的分支结构广义香加起着这些熵的确定至关重要的作用。

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