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
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;
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
DOI :
10.1109/ISIT.2006.261685
