A new treatment of convex functions

M. Sababheh, Shigeru Furuichi, H. Moradi
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引用次数: 1

Abstract

Convex functions have played a major role in the field of Mathematical inequalities. In this paper, we introduce a new concept related to convexity, which proves better estimates when the function is somehow more convex than another. In particular, we define what we called $g-$convexity as a generalization of $\log-$convexity. Then we prove that $g-$convex functions have better estimates in certain known inequalities like the Hermite-Hadard inequality, super additivity of convex functions, the Majorization inequality and some means inequalities. Strongly related to this, we define the index of convexity as a measure of ``how much the function is convex". Applications including Hilbert space operators, matrices and entropies will be presented in the end.
凸函数的一种新处理
凸函数在数学不等式领域中起着重要的作用。在本文中,我们引入了一个关于凸性的新概念,它证明了当函数比另一个函数更凸时更好的估计。特别地,我们将所谓的$g-$凸性定义为$\log-$凸性的泛化。然后证明了$g-$凸函数在某些已知不等式中有较好的估计,如Hermite-Hadard不等式、凸函数的超可加性、多数化不等式和一些均值不等式。与此密切相关的是,我们将凸度指数定义为“函数凸的程度”的度量。应用包括希尔伯特空间算子,矩阵和熵将在最后提出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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