DocumentCode
2940329
Title
On Information Divergence Measures and a Unified Typicality
Author
Ho, Siu-Wai ; Yeung, Raymond W.
Author_Institution
Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin
fYear
2006
fDate
9-14 July 2006
Firstpage
113
Lastpage
117
Abstract
Strong typicality, which is more powerful for theorem proving than the weak typicality, can be applied to finite alphabet only, while weak typicality can be applied to both finite and countably infinite alphabets. In this paper, the relation between typicality and information divergence measures is discussed. This leads to the definition of a unified typicality for finite or countably infinite alphabet which is stronger than both weak typicality and strong typicality
Keywords
entropy; entropy; infinite alphabet; information divergence measures; Entropy; Information theory; Power engineering and energy; Probability distribution; Random variables; Source coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2006 IEEE International Symposium on
Conference_Location
Seattle, WA
Print_ISBN
1-4244-0505-X
Electronic_ISBN
1-4244-0504-1
Type
conf
DOI
10.1109/ISIT.2006.261685
Filename
4035932
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