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Related papers: Entropy functions and functional equations

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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

A method of estimating the joint probability mass function of a pair of discrete random variables is described. This estimator is used to construct the conditional Shannon-R\'eyni-Tsallis entropies estimates. From there almost sure rates of…

Statistics Theory · Mathematics 2020-02-18 Ba Amadou Diadie , Lo Gane Samb

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

The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair Entropy-Statistical Complexity for a large class…

In a recent paper [Entropy 2020, 22(1), 17] C. Tsallis states that entropy -- as in Shannon's or Kullback-Leiber's definitions -- is inadequate to interpret black hole entropy and suggests that a new non-additive functional should take the…

General Relativity and Quantum Cosmology · Physics 2021-03-23 Pedro Pessoa , Bruno Arderucio Costa

The paper suggests the concepts of an upper entropy and a lower entropy. We propose a new axiomatic definition, namely, upper entropy axioms, inspired by axioms of metric spaces, and also formulate lower entropy axioms. We also develop weak…

Probability · Mathematics 2015-06-22 Jin-Li Guo , Qi Suo

We consider the problem of finite sample corrections for entropy estimation. New estimates of the Shannon entropy are proposed and their systematic error (the bias) is computed analytically. We find that our results cover correction…

Statistical Mechanics · Physics 2009-11-10 Thomas Schürmann

It is well-known that the Shannon entropies of some parameterized probability distributions are concave functions with respect to the parameter. In this paper we consider a family of such distributions (including the binomial, Poisson, and…

Classical Analysis and ODEs · Mathematics 2016-08-19 Ioan Rasa

We propose a new way of defining entropy of a system, which gives a general form which may be nonextensive as Tsallis entropy, but is linearly dependent on component entropies, like Renyi entropy, which is extensive. This entropy has a…

Adaptation and Self-Organizing Systems · Physics 2007-10-11 Fariel Shafee

Entropic uncertainty relations are interesting in their own rights as well as for a lot of applications. Keeping this in mind, we try to make the corresponding inequalities as tight as possible. The use of parametrized entropies also allows…

Quantum Physics · Physics 2023-05-30 Alexey E. Rastegin

Entropy functionals (i.e. convex integral functionals) and extensions of these functionals are minimized on convex sets. This paper is aimed at reducing as much as possible the assumptions on the constraint set. Dual equalities and…

Optimization and Control · Mathematics 2015-05-13 Christian Léonard

Here we explain how C. Tsallis' reply (Entropy 2021, 23(5), 630) fails to respond to points raised in (Entropy 2020, 22(10), 1110) and introduces further inconsistencies on the origin of black hole entropy. In his reply, Tsallis argues that…

General Relativity and Quantum Cosmology · Physics 2022-10-04 Pedro Pessoa , Bruno Arderucio Costa , Steve Pressé

The problem of Shannon entropy estimation in countable infinite alphabets is addressed from the study and use of convergence results of the entropy functional, which is known to be discontinuous with respect to the total variation distance…

Information Theory · Computer Science 2018-04-03 Jorge F. Silva

The Shannon-Khinchin axioms for the ordinary information entropy are generalized in a natural way to the nonextensive systems based on the concept of nonextensive conditional entropy, and a complete proof of the uniqueness theorem for the…

Statistical Mechanics · Physics 2009-10-31 Sumiyoshi Abe

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

The notion of group entropy is proposed. It enables to unify and generalize many different definitions of entropy known in the literature, as those of Boltzmann-Gibbs, Tsallis, Abe and Kaniadakis. Other new entropic functionals are…

Statistical Mechanics · Physics 2015-05-28 Piergiulio Tempesta

This study introduces the syntropy function ($S_N$) and expectancy function ($E_N$), derived from the novel function $\phi$, to provide a refined perspective on complexity, extending beyond conventional entropy analysis. $S_N$ is designed…

Statistical Mechanics · Physics 2024-03-21 Santiago Mendez-Moreno

Recently, Suyari has proposed a generalization of Shannon-Khinchin axioms, which determines a class of entropies containing the well-known Tsalis and Havrda-Charvat entropies [H. Suyari, IEEE Trans. Inf. Theory, vol. 50, pp. 1783-1787, Aug.…

Mathematical Physics · Physics 2012-12-03 Velimir M. Ilic , Miomir S. Stankovic , Edin H. Mulalic

We present our view in a standing debate about the definition and meaning of power-law entropies for continuous systems. Our suggestion is that such arguments should take into account the generalized operations of addition and…

Statistical Mechanics · Physics 2018-10-17 Anthony J. Creaco , Nikolaos Kalogeropoulos

In recent years, learning for neural networks can be viewed as optimization in the space of probability measures. To obtain the exponential convergence to the optimizer, the regularizing term based on Shannon entropy plays an important…

Machine Learning · Statistics 2024-11-07 Keito Akiyama