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Proving Information Inequalities by Gaussian Elimination

Information Theory 2024-01-29 v1 math.IT

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.

Keywords

Cite

@article{arxiv.2401.14916,
  title  = {Proving Information Inequalities by Gaussian Elimination},
  author = {Laigang Guo and Raymond W. Yeung and Xiao-Shan Gao},
  journal= {arXiv preprint arXiv:2401.14916},
  year   = {2024}
}

Comments

arXiv admin note: text overlap with arXiv:2202.02786

R2 v1 2026-06-28T14:28:13.577Z