Refined Young inequality and its application to divergences

04/27/2021
by   Shigeru Furuichi, et al.
0

We give bounds on the difference between the weighted arithmetic mean and the weighted geometric mean. These imply refined Young inequalities and the reverses of the Young inequality. We also study some properties on the difference between the weighted arithmetic mean and the weighted geometric mean. Applying the newly obtained inequalities, we show some results on the Tsallis divergence, the Rényi divergence, the Jeffreys-Tsallis divergence and the Jensen-Shannon-Tsallis divergence.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/09/2021

On some tensor inequalities based on the t-product

In this work, we investigate the tensor inequalities in the tensor t-pro...
research
03/20/2019

Inequalities related to some types of entropies and divergences

The aim of this paper is to discuss new results concerning some kinds of...
research
04/07/2019

Statistical Meaning of Mean Functions

The basic properties of the Fisher information allow to reveal the stati...
research
03/29/2021

Exact converses to a reverse AM–GM inequality, with applications to sums of independent random variables and (super)martingales

For every given real value of the ratio μ:=A_X/G_X>1 of the arithmetic a...
research
06/02/2020

Recht-Ré Noncommutative Arithmetic-Geometric Mean Conjecture is False

Stochastic optimization algorithms have become indispensable in modern m...
research
07/29/2019

Diffusion Hypercontractivity via Generalized Density Manifold

We prove a one-parameter family of diffusion hypercontractivity and pres...
research
01/27/2020

The α-divergences associated with a pair of strictly comparable quasi-arithmetic means

We generalize the family of α-divergences using a pair of strictly compa...

Please sign up or login with your details

Forgot password? Click here to reset