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  • 标题:Generalized Mutual Information
  • 本地全文:下载
  • 作者:Zhiyi Zhang
  • 期刊名称:Stats
  • 电子版ISSN:2571-905X
  • 出版年度:2020
  • 卷号:3
  • 期号:2
  • 页码:158-165
  • DOI:10.3390/stats3020013
  • 出版社:MDPI AG
  • 摘要:Mutual information is one of the essential building blocks of information theory. It is however only finitely defined for distributions in a subclass of the general class of all distributions on a joint alphabet. The unboundedness of mutual information prevents its potential utility from being extended to the general class. This is in fact a void in the foundation of information theory that needs to be filled. This article proposes a family of generalized mutual information whose members are indexed by a positive integer n, with the nth member being the mutual information of nth order. The mutual information of the first order coincides with Shannon’s, which may or may not be finite. It is however established (a) that each mutual information of an order greater than 1 is finitely defined for all distributions of two random elements on a joint countable alphabet, and (b) that each and every member of the family enjoys all the utilities of a finite Shannon’s mutual information.
  • 关键词:mutual information; Shannon’s entropy; conditional distribution of total collision; generalized entropy; generalized mutual information
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