Proving Information Inequalities by Gaussian Elimination

IF 2.2 3区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Transactions on Information Theory Pub Date : 2025-01-17 DOI:10.1109/TIT.2025.3531133

Laigang Guo;Raymond W. Yeung;Xiao-Shan Gao

引用次数: 0

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). Building on our recent work (Guo et al., 2023), we developed in this paper an enhanced approach for solving this problem. Experimental results show that our new approach improves the time complexity by over 500 times compared with Guo et al. (2023) for the problem studied by Tian (2014).

查看原文本刊更多论文

在信息度量的线性约束下证明信息不等式和等式是信息论中的一个重要问题。为此，人们开发并实现了 ITIP 算法和其他变体算法，它们都基于线性规划（LP）的求解。在我们最近的工作（Guo 等人，2023 年）基础上，我们在本文中开发了一种解决该问题的增强方法。实验结果表明，对于 Tian（2014）研究的问题，我们的新方法与 Guo 等人（2023）的方法相比，时间复杂度提高了 500 多倍。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Information Theory 工程技术-工程：电子与电气

CiteScore

5.70

自引率

20.00%

发文量

514

审稿时长

12 months

期刊介绍： The IEEE Transactions on Information Theory is a journal that publishes theoretical and experimental papers concerned with the transmission, processing, and utilization of information. The boundaries of acceptable subject matter are intentionally not sharply delimited. Rather, it is hoped that as the focus of research activity changes, a flexible policy will permit this Transactions to follow suit. Current appropriate topics are best reflected by recent Tables of Contents; they are summarized in the titles of editorial areas that appear on the inside front cover.