DocumentCode
3505734
Title
On essentially conditional information inequalities
Author
Kaced, Tarik ; Romashchenko, Andrei
Author_Institution
LIF de Marseille, Univ. Aix-Marseille, Marseille, France
fYear
2011
fDate
July 31 2011-Aug. 5 2011
Firstpage
1935
Lastpage
1939
Abstract
In 1997, Z. Zhang and R.W. Yeung found the first example of a conditional information inequality in four variables that is not “Shannon-type”. This linear inequality for entropies is called conditional (or constraint) since it holds only under condition that some linear equations are satisfied for the involved entropies. Later, the same authors and other researchers discovered several unconditional information inequalities that do not follow from Shannon´s inequalities for entropy. In this paper we show that some non Shannon-type conditional inequalities are “essentially” conditional, i.e., they cannot be extended to any unconditional inequality. We prove one new essentially conditional information inequality for Shannon´s entropy and discuss conditional information inequalities for Kolmogorov complexity.
Keywords
computational complexity; entropy; Kolmogorov complexity; Shannon entropy; conditional information inequality; entropy; linear equation; linear inequality; Cloning; Complexity theory; Cramer-Rao bounds; Entropy; Joints; Mutual information; Random variables;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on
Conference_Location
St. Petersburg
ISSN
2157-8095
Print_ISBN
978-1-4577-0596-0
Electronic_ISBN
2157-8095
Type
conf
DOI
10.1109/ISIT.2011.6033889
Filename
6033889
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