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Information inequalities govern the ultimate limitations in information theory and as such play an pivotal role in characterizing what values the entropy of multipartite states can take. Proving an information inequality, however, quickly…

Quantum Physics · Physics 2025-10-23 Shao-Lun Huang , Tobias Rippchen , Mario Berta

In this work we study zero vs. epsilon-error capacity in network coding instances. For multicast network coding it is well known that all rates that can be delivered with arbitrarily small error probability can also be delivered with zero…

Information Theory · Computer Science 2015-03-19 Michael Langberg , Michelle Effros

Entropic measures of complexity are able to quantify the information encoded in complex network structures. Several entropic measures have been proposed in this respect. Here we study the relation between the Shannon entropy and the Von…

Disordered Systems and Neural Networks · Physics 2011-09-30 Kartik Anand , Ginestra Bianconi , Simone Severini

In this work we prove that the possibility of superactivation of quantum channel capacities is determined by the mathematical properties of the quantum relative entropy function. Before our work this fundamental and purely mathematical…

Quantum Physics · Physics 2012-06-26 Laszlo Gyongyosi , Sandor Imre

This paper considers an information bottleneck problem with the objective of obtaining a most informative representation of a hidden feature subject to a R\'enyi entropy complexity constraint. The optimal bottleneck trade-off between…

Information Theory · Computer Science 2021-02-01 Jian-Jia Weng , Fady Alajaji , Tamás Linder

It has been demonstrated that excitable media with a tree structure performed better than other network topologies, it is natural to consider neural networks defined on Cayley trees. The investigation of a symbolic space called tree-shift…

Dynamical Systems · Mathematics 2018-02-28 Jung-Chao Ban , Chih-Hung Chang , Nai-Zhu Huang

We show how the Shannon entropy function can be used as a basis to set up complexity measures weighting the economic efficiency of countries and the specialization of products beyond bare diversification. This entropy function guarantees…

Physics and Society · Physics 2021-06-04 Gianluca Teza , Michele Caraglio , Attilio L. Stella

Understanding the structural complexity and predictability of complex networks is a central challenge in network science. Although recent studies have revealed a relationship between compression-based entropy and link prediction…

Social and Information Networks · Computer Science 2025-10-14 Sebastián Brzovic , Cristóbal Rojas , Andrés Abeliuk

Recent research has demonstrated significant achievable performance gains by exploiting circularity/non-circularity or propeness/improperness of complex-valued signals. In this paper, we investigate the influence of these properties on…

Information Theory · Computer Science 2016-11-17 Georg Tauboeck

We consider the entropy of sums of independent discrete random variables, in analogy with Shannon's Entropy Power Inequality, where equality holds for normals. In our case, infinite divisibility suggests that equality should hold for…

Information Theory · Computer Science 2010-10-21 Oliver Johnson , Yaming Yu

The purpose of this note is to establish a connection between the problem of reliability (when there is an intermittent control-input channel failure that may occur between actuators, controllers and/or sensors in the system) and the notion…

Dynamical Systems · Mathematics 2013-03-12 Getachew K Befekadu

In part I, we reviewed how Shannon's classical notion of capacity is not sufficient to characterize a noisy communication channel if the channel is intended to be used as part of a feedback loop to stabilize an unstable scalar linear…

Information Theory · Computer Science 2007-12-06 Anant Sahai , Sanjoy Mitter

We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We show that our bound can outperform both the Lov\'asz theta number and the Haemers minimum rank bound. As a by-product, we also obtain a new…

Information Theory · Computer Science 2018-09-07 Sihuang Hu , Itzhak Tamo , Ofer Shayevitz

Using the concept of discrete noiseless channels, it was shown by Shannon in A Mathematical Theory of Communication that the ultimate performance of an encoder for a constrained system is limited by the combinatorial capacity of the system…

Information Theory · Computer Science 2008-09-09 Georg Böcherer , Valdemar Cardoso da Rocha , Cecilio Pimentel

It is already known that in multicast (single source, multiple sinks) network, random linear network coding can achieve the maximum flow upper bound. In this paper, we investigate how random linear network coding behaves in general…

Information Theory · Computer Science 2012-10-09 Yuan Li

The field of information science has greatly developed, and applications in various fields have emerged. In this paper, we evaluated the coding system in the theory of Tsallis entropy for transmission of messages and aimed to formulate the…

Molecular Networks · Quantitative Biology 2017-12-13 Tatsuaki Tsuruyama

Accurate fading characterization and channel capacity determination are of paramount importance in both conventional and emerging communication systems. The present work addresses the nonlinearity of the propagation medium and its effects…

Information Theory · Computer Science 2016-12-30 Paschalis C. Sofotasios , Sami Muhaidat , Mikko Valkama , Mounir Ghogho , George K. Karagiannidis

In a network, a channel introduces correlations to the parties that aim to establish a communication protocol. In this work, we present a framework of non-local network coding by exploiting a Bell scenario and show the usefulness of…

Quantum Physics · Physics 2020-10-14 Jiyoung Yun , Ashutosh Rai , Joonwoo Bae

Quantum entropy inequalities are studied. Some quantum entropy inequalities are obtained by several methods. For entanglement breaking channel, we show that the entanglement-assisted classical capacity is upper bounded by $\log d$. A…

Quantum Physics · Physics 2009-11-07 Heng Fan

I consider the effect of a finite sample size on the entropy of a sample of independent events. I propose formula for entropy which satisfies Shannon's axioms, and which reduces to Shannon's entropy when sample size is infinite. I discuss…

Information Theory · Computer Science 2015-04-08 Sergei Viznyuk