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We propose a compression-based version of the empirical entropy of a finite string over a finite alphabet. Whereas previously one considers the naked entropy of (possibly higher order) Markov processes, we consider the sum of the…

Information Theory · Computer Science 2011-04-05 Paul M. B. Vitányi

We develop a reverse entropy power inequality for convex measures, which may be seen as an affine-geometric inverse of the entropy power inequality of Shannon and Stam. The specialization of this inequality to log-concave measures may be…

Functional Analysis · Mathematics 2012-04-02 Sergey Bobkov , Mokshay Madiman

It is well known that there is a strong connection between entropy inequalities and submodularity, since the entropy of a collection of random variables is a submodular function. Unifying frameworks for information inequalities arising from…

Information Theory · Computer Science 2026-01-23 Gunank Jakhar , Gowtham R. Kurri , Suryajith Chillara , Vinod M. Prabhakaran

In this work, we study generalized entropies and information geometry in a group-theoretical framework. We explore the conditions that ensure the existence of some natural properties and at the same time of a group-theoretical structure for…

Mathematical Physics · Physics 2021-08-03 Miguel A. Rodríguez , Álvaro Romaniega , Piergiulio Tempesta

This study is an example of a solid connection between fractional analysis and inequality theory, and includes new inequalities of the P\'{o}lya-Szeg% \"{o}-Chebyshev type obtained with the help of Generalized Proportional Fractional…

General Mathematics · Mathematics 2020-06-09 Saad Ihsan Butt , Ahmet Ocak Akdemir , Alper Ekinci , Muhammad Nadeem

Number-phase uncertainty relations are formulated in terms of unified entropies which form a family of two-parametric extensions of the Shannon entropy. For two generalized measurements, unified-entropy uncertainty relations are given in…

Quantum Physics · Physics 2012-06-26 Alexey E. Rastegin

We study how the Shannon entropy of sequences produced by an information source converges to the source's entropy rate. We synthesize several phenomenological approaches to applying information theoretic measures of randomness and memory to…

Statistical Mechanics · Physics 2007-05-23 James P. Crutchfield , David P. Feldman

Fano's inequality is one of the most elementary, ubiquitous, and important tools in information theory. Using majorization theory, Fano's inequality is generalized to a broad class of information measures, which contains those of Shannon…

Information Theory · Computer Science 2020-08-04 Yuta Sakai

In a series of works, Lutwak, Yang and Zhang established what could be called affine information theory, which is the study of moment-entropy and Fisher-information-type inequalities that are invariant with respect to affine transformations…

Functional Analysis · Mathematics 2025-03-04 Dylan Langharst

We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global…

Molecular Networks · Quantitative Biology 2015-12-14 Hector Zenil , Narsis A. Kiani , Jesper Tegnér

In this study, we obtain some new integral inequalities for different classes of convex functions by using some elementary inequalities and classical inequalities like general Cauchy inequality and Minkowski inequality.

Classical Analysis and ODEs · Mathematics 2012-02-10 M. Emin Ozdemir , Alper Ekinci , Ahmet Ocak Akdemir

There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as…

Information Theory · Computer Science 2011-11-29 David Balduzzi

Shannon's Entropy Power Inequality can be viewed as characterizing the minimum differential entropy achievable by the sum of two independent random variables with fixed differential entropies. The entropy power inequality has played a key…

Information Theory · Computer Science 2012-07-31 Varun Jog , Venkat Anantharam

We present a quantum information theory that allows for a consistent description of entanglement. It parallels classical (Shannon) information theory but is based entirely on density matrices (rather than probability distributions) for the…

Quantum Physics · Physics 2009-10-30 Nicolas J. Cerf , Chris Adami

Researchers have proposed formal definitions of quantitative information flow based on information theoretic notions such as the Shannon entropy, the min entropy, the guessing entropy, and channel capacity. This paper investigates the…

Cryptography and Security · Computer Science 2010-04-02 Hirotoshi Yasuoka , Tachio Terauchi

This preprint is a text for students and teachers on inequalities. Some standard topics are covered on application of calculus to inequality proving. Many examples are considered, stated, solved or partially solved. Some problems are…

History and Overview · Mathematics 2022-09-07 Sergei Sitnik , Elina Shishkina , Lidiya Kovaleva , Olga Chernova

Uncertainty relations are central to quantum physics. While they were originally formulated in terms of variances, they have later been successfully expressed with entropies following the advent of Shannon information theory. Here, we…

Quantum Physics · Physics 2019-05-01 Anaelle Hertz , Nicolas J. Cerf

The minimal set of Shannon-type inequalities (referred to as elemental inequalities), plays a central role in determining whether a given inequality is Shannon-type. Often, there arises a situation where one needs to check whether a given…

Information Theory · Computer Science 2017-06-13 Satyajit Thakor , Terence Chan , Alex Grant

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

We have presented a new axiomatic derivation of Shannon Entropy for a discrete probability distribution on the basis of the postulates of additivity and concavity of the entropy function.We have then modified shannon entropy to take account…

Quantum Physics · Physics 2007-05-23 C. G. Chakrabarti , Indranil Chakrabarty