一种双参数熵及其基本性质
A two-parameter entropy and its fundamental properties
AI总结：
本文提出一种可退化为Tsallis熵和Shannon熵的双参数广义熵，系统研究其信息论与信息几何性质，并证明其满足次可加性、强次可加性、联合凸性和信息单调性。
摘要：
本文提出了一种新的双参数广义熵，当参数取特定值时，它可以退化为Tsallis熵和Shannon熵。我们发展了这种广义熵及其散度的若干信息论性质，例如次可加性、强次可加性、联合凸性和信息单调性。本文对这种新广义熵的信息论与信息几何特征进行了阐述性研究，并将其与Tsallis熵和Shannon熵的性质进行了比较。
英文摘要：
This article proposes a new two-parameter generalized entropy, which can be reduced to the Tsallis and the Shannon entropy for specific values of its parameters. We develop a number of information-theoretic properties of this generalized entropy and divergence, for instance, the sub-additive property, strong sub-additive property, joint convexity, and information monotonicity. This article presents an exposit investigation on the information-theoretic and information-geometric characteristics of the new generalized entropy and compare them with the properties of the Tsallis and the Shannon entropy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
