Proving Information Inequalities by Gaussian Elimination
CoRR(2024)
Abstract
The proof of information inequalities and identities under linear constraints
on the information measures is an important problem in information theory. For
this purpose, ITIP and other variant algorithms have been developed and
implemented, which are all based on solving a linear program (LP). In this
paper, we develop a method with symbolic computation. Compared with the known
methods, our approach can completely avoids the use of linear programming which
may cause numerical errors. Our procedures are also more efficient
computationally.
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