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In this paper the author analyses the weighted Renyi entropy in order to derive several inequalities in weighted case. Furthermore, using the proposed notions $\alpha$-th generalized derivation and ($\alpha$; p)-th weighted Fisher…

Information Theory · Computer Science 2015-10-16 Salimeh Yasaei Sekeh

The notion of weighted quantum entropy is reviewed and considered for bipartite and noncomposite quantum systems. The known for the weighted entropy information inequality (subadditivity condition) is extended to the case of indivisible…

Quantum Physics · Physics 2016-10-25 V. I. Man'ko , Z. Seilov

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

This paper represents an extended version of an earlier note [10]. The concept of weighted entropy takes into account values of different outcomes, i.e., makes entropy context-dependent, through the weight function. We analyse analogs of…

Probability · Mathematics 2017-10-31 Mark Kelbert , Izabella Stuhl , Yuri Suhov

We develop an information-theoretic perspective on some questions in convex geometry, providing for instance a new equipartition property for log-concave probability measures, some Gaussian comparison results for log-concave measures, an…

Functional Analysis · Mathematics 2011-03-31 Sergey Bobkov , Mokshay Madiman

Following [1], the aim of this paper is to analyze the relative weighted entropy involving the central moments weight functions. We compare the standard relative entropy with the weighted case in two particular forms of Gaussian…

Information Theory · Computer Science 2015-06-23 Salimeh Yasaei Sekeh , Adriano Polpo

Weighted Updating generalizes Bayesian updating, allowing for biased beliefs by weighting the likelihood function and prior distribution with positive real exponents. I provide a rigorous foundation for the model by showing that…

Probability · Mathematics 2016-02-09 Jesse Aaron Zinn

The entropy power inequality for independent random vectors is a foundational result of information theory, with deep connections to probability and geometric functional analysis. Several extensions of the entropy power inequality have been…

Information Theory · Computer Science 2025-12-23 Mokshay Madiman , James Melbourne , Cyril Roberto

In this paper, we review Fisher information matrices properties in weighted version and discuss inequalities/bounds on it by using reduced weight functions. In particular, an extended form of the Fisher information inequality previously…

Information Theory · Computer Science 2016-02-01 Mark Kelbert , Yuri Suhov , Salimeh Yasaei Sekeh

We establish a general class of entropy inequalities that take the concise form of Gaussian comparisons. The main result unifies many classical and recent results, including the Shannon-Stam inequality, the Brunn-Minkowski inequality, the…

Information Theory · Computer Science 2022-06-29 Efe Aras , Thomas A. Courtade

We derive new inequalities for the probabilities of projective measurements in mutually unbiased bases of a qudit system. These inequalities lead to wider ranges of validity and tighter bounds on entropic uncertainty inequalities previously…

Quantum Physics · Physics 2009-11-13 Shengjun Wu , Sixia Yu , Klaus Mølmer

Motivated by the entropy computations relevant to the evaluation of decrease in entropy in bit reset operations, the authors investigate the deficit in an entropic inequality involving two independent random variables, one continuous and…

Information Theory · Computer Science 2018-09-21 James Melbourne , Saurav Talukdar , Shreyas Bhaban , Murti V. Salapaka

Motivated by fractal geometry of self-affine carpets and sponges, Feng--Huang (2016) introduced weighted topological entropy and pressure for factor maps between dynamical systems, and proved variational principles for them. We introduce a…

Dynamical Systems · Mathematics 2021-08-10 Masaki Tsukamoto

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

We generalize, improve and unify theorems of Rumin, and Maassen--Uffink about classical entropies associated to quantum density matrices. These theorems refer to the classical entropies of the diagonals of a density matrix in two different…

Mathematical Physics · Physics 2015-05-30 Rupert L. Frank , Elliott H. Lieb

We establish analogues of the Bergstr\"om and Bonnesen inequalities, related to determinants and volumes respectively, for the entropy power and for the Fisher information. The obtained inequalities strengthen the well-known convolution…

Information Theory · Computer Science 2025-01-20 Matthieu Fradelizi , Lampros Gavalakis , Martin Rapaport

We consider a "length-biased" shift-dependent information measure, related to the differential entropy in which higher weight is assigned to large values of observed random variables. This allows us to introduce the notions of "weighted…

Statistics Theory · Mathematics 2011-06-27 Antonio Di Crescenzo , Maria Longobardi

A framework for deriving R\'enyi entropy-power inequalities (EPIs) is presented that uses linearization and an inequality of Dembo, Cover, and Thomas. Simple arguments are given to recover the previously known R\'enyi EPIs and derive new…

Information Theory · Computer Science 2020-04-08 Olivier Rioul

We tighten the Entropy Power Inequality (EPI) when one of the random summands is Gaussian. Our strengthening is closely connected to the concept of strong data processing for Gaussian channels and generalizes the (vector extension of)…

Information Theory · Computer Science 2016-02-10 Thomas A. Courtade

A new determinant inequality of positive semidefinite matrices is discovered and proved by us. This new inequality is useful for attacking and solving a variety of optimization problems arising from the design of wireless communication…

Information Theory · Computer Science 2012-07-18 Jun Fang , Hongbin Li
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