By Topic

A framework for linear information inequalities

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
R. W. Yeung ; Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong

We present a framework for information inequalities, namely, inequalities involving only Shannon's information measures, for discrete random variables. A region in IR(2n-1), denoted by Γ*, is identified to be the origin of all information inequalities involving n random variables in the sense that all such inequalities are partial characterizations of Γ*. A product from this framework is a simple calculus for verifying all unconstrained and constrained linear information identities and inequalities which can be proved by conventional techniques. These include all information identities and inequalities of such types in the literature. As a consequence of this work, most identities and inequalities involving a definite number of random variables can now be verified by a software called ITIP which is available on the World Wide Web. Our work suggests the possibility of the existence of information inequalities which cannot be proved by conventional techniques. We also point out the relation between Γ* and some important problems in probability theory and information theory

Published in:

IEEE Transactions on Information Theory  (Volume:43 ,  Issue: 6 )