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Maximal repetition of a string is the maximal length of a repeated substring. This paper investigates maximal repetition of strings drawn from stochastic processes. Strengthening previous results, two new bounds for the almost sure growth…

Information Theory · Computer Science 2020-03-11 Łukasz Dębowski

In many applications, the probability density function is subject to experimental errors. In this work the continuos dependence of a class of generalized entropies on the experimental errors is studied. This class includes the C. Shannon,…

Data Analysis, Statistics and Probability · Physics 2016-05-20 György Steinbrecher , Giorgio Sonnino

Data partitioning that maximizes/minimizes the Shannon entropy, or more generally the R\'enyi entropy is a crucial subroutine in data compression, columnar storage, and cardinality estimation algorithms. These partition algorithms can be…

Data Structures and Algorithms · Computer Science 2025-11-05 Aryan Esmailpour , Sanjay Krishnan , Stavros Sintos

The diversity of a community that cannot be fully counted must be inferred. The two preeminent inference methods are the MaxEnt method, which uses information in the form of constraints and Bayes' rule which uses information in the form of…

Methodology · Statistics 2008-08-25 Adom Giffin

We consider the concept of generalized measure-theoretic entropy, where instead of the Shannon entropy function we consider an arbitrary concave function defined on the unit interval, vanishing in the origin. Under mild assumptions on this…

Dynamical Systems · Mathematics 2014-08-21 Fryderyk Falniowski

The Renyi, Shannon and Fisher spreading lengths of the classical or hypergeometric orthogonal polynomials, which are quantifiers of their distribution all over the orthogonality interval, are defined and investigated. These…

Mathematical Physics · Physics 2009-11-11 P. Sánchez-Moreno , J. S. Dehesa , D. Manzano , R. Yáñez

We study a quantity called discrete layered entropy, which approximates the Shannon entropy within a logarithmic gap. Compared to the Shannon entropy, the discrete layered entropy is piecewise linear, approximates the expected length of the…

Information Theory · Computer Science 2026-01-27 Cheuk Ting Li

We introduce unbiased estimators for the Shannon entropy and the class number, in the situation that we are able to take sequences of independent samples of arbitrary length.

Statistics Theory · Mathematics 2014-10-21 Stephen Montgomery-Smith , T. Schürmann

The Tsallis entropy is shown to be an additive entropy of degree-q that information scientists have been using for almost forty years. Neither is it a unique solution to the nonadditive functional equation from which random entropies are…

Classical Physics · Physics 2016-11-15 B. H. Lavenda , J. Dunning-Davies

We study analytically the corrections to the leading terms in the Renyi entropy of a massive lattice theory, showing significant deviations from naive expectations. In particular, we show that finite size and finite mass effects give rise…

High Energy Physics - Theory · Physics 2012-05-31 Elisa Ercolessi , Stefano Evangelisti , Fabio Franchini , Francesco Ravanini

We share a small connection between information theory, algebra, and topology - namely, a correspondence between Shannon entropy and derivations of the operad of topological simplices. We begin with a brief review of operads and their…

Algebraic Topology · Mathematics 2021-09-13 Tai-Danae Bradley

This study focuses on conditional entropy frameworks based on the Kolmogorov--Nagumo (KN) mean. First, $(\eta, \psi)$-KN averaging (\texttt{EPKNAVG}), a KN-mean extension of the $\eta$-averaging (\texttt{EAVG}) framework for $(\eta,…

Information Theory · Computer Science 2026-05-13 Akira Kamatsuka , Takahiro Yoshida

We establish a discrete analog of the R\'enyi entropy comparison due to Bobkov and Madiman. For log-concave variables on the integers, the min entropy is within log e of the usual Shannon entropy. Additionally we investigate the entropic…

Probability · Mathematics 2021-06-01 James Melbourne , Tomasz Tkocz

Let $A$ and $B$ be two accretive operators. We first introduce the weighted geometric mean of $A$ and $B$ together with some related properties. Afterwards, we define the relative entropy as well as the Tsallis entropy of $A$ and $B$. The…

Functional Analysis · Mathematics 2021-07-23 M. Raïssouli , M. S. Moslehian , S. Furuichi

Existing polarization theories have mostly been concerned with Shannon's information measures, such as Shannon entropy and mutual information, and some related measures such as the Bhattacharyya parameter. In this work, we extend…

Information Theory · Computer Science 2019-07-16 Mengfan Zheng , Ling Liu , Cong Ling

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory,…

Machine Learning · Statistics 2025-03-06 Salomé A. Sepúveda Fontaine , José M. Amigó

The concept of weighted entropy takes into account values of different outcomes, i.e., makes entropy context-dependent, through the weight function. In this paper, we establish a number of simple inequalities for the weighted entropies…

Information Theory · Computer Science 2016-01-15 Yuri Suhov , Izabella Stuhl , Salimeh Yasaei Sekeh , Mark Kelbert

Pseudoentropy characterizations provide a quantitatively precise demonstration of the close relationship between computational hardness and computational randomness. We prove a unified pseudoentropy characterization that generalizes and…

Computational Complexity · Computer Science 2025-09-05 Lunjia Hu , Salil Vadhan

We discuss the properties of invariant measures corresponding to iterated function systems (IFSs) with place-dependent probabilities and compute their Renyi entropies, generalized dimensions, and multifractal spectra. It is shown that with…

chao-dyn · Physics 2009-10-31 Wojciech Slomczynski , Jaroslaw Kwapien , Karol Zyczkowski

In computer vision, it is often observed that formulating regression problems as a classification task often yields better performance. We investigate this curious phenomenon and provide a derivation to show that classification, with the…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Shihao Zhang , Linlin Yang , Michael Bi Mi , Xiaoxu Zheng , Angela Yao