GM-凸函数及其Jensen型不等式

作为对几何凸函数、GA-凸函数、GH-凸函数的推广,提出了GM-凸函数的概念,并研究了它的性质及其判定,进而建立了GM-凸函数的离散型Jensen不等式,并给出若干应用.     

凸函数的双参数Jensen不等式链

使用组合理论,将凸函数的单参数Jensen不等式链推广为双参数的形式,从而获得一个新的Jensen不等式链.     

关于几何凸函数的Jensen不等式的加细

利用几何凸函数的Jensen不等式建立一个由{1,2,…,n}到(0,+∞)上的一个映射,研究了这个映射的单调性,获得一个该Jensen不等式的加细,并得到几何凸函数的一些新的不等式.     

一个三角形几何不等式的推广

首先从第3届国际数学奥林匹克IMO竞赛命题中一个三角形几何不等式出发,将问题推广到对更一般的三角几何不等式及多边形几何不等式的研究.然后利用凸函数的Jensen不等式,得到更一般的三角形几何不等式及圆外切多边形几何不等式,推广了原命题.     

基于平方凸函数的Lyapunov型不等式

本文研究了一类非线性系统,引入了平方凸函数推广凸函数,基于平方凸函数建立了新的Lyapunov不等式．     

广义凸函数的特征性质

提出广义凸集、广义凸函数、中间点广义凸函数、端点广义凸函数四个定义,通过定义条件P1,研究条件P1所蕴含的等式关系,进而得到一个基础性定理一稠密性定理和一个相对条件较弱的推论,最后将结果应用于若干不同类型的广义凸函数类,尤其是s-凸函数、几何凸函数、rp-凸函数,得到它们所共有的一个特征性质,即满足稠密性定理．     

由凸函数引起相关不等式的思考

在学习一元微分学的凸函数中引起思考,从其定义和判定定理出发,进一步学习探索Jensen不等式,并体会凸函数和Jensen不等式在很多经典不等式证明中的作用.     

HG凸函数的Hermite-Hadamard型不等式

利用Cauchy-Schwarz不等式、Young不等式和HG凸函数定义,得到几个HG凸函数的Hermite-Hadamard型不等式.     

关于两个凸函数乘积的不等式

针对两个正的连续凸函数,利用各自的算术平均值,给出它们乘积的算术平均值的上界.在这两个凸函数成似序时,这个上界比由Hermite-Hadamard不等式得到的上界要小.在这两个凸函数成反序时,这个上界与由Chebyshev不等式得到的上界各有强弱.     

两个反三角平均的Schur凸性及不等式链

关于张帆,钱伟茂所定义的四个反三角函数平均,利用Hermite-Hadamard不等式证得其中两个反三角平均:Marcsin(a,b)分别是Schur-凸,Schur-几何凸,Schur-调和凸;Marctan(a,b)分别是Schur-凹,Schur-几何凸,Schur-调和凸,并结合凸函数理论得出若干不等式链.     

Geometrically concave univariate distributions

In this paper our aim is to show that if a probability density function is geometrically concave (convex), then the corresponding cumulative distribution function and the survival function are geometrically concave (convex) too, under some assumptions. The proofs are based on the so-called monotone form of l'Hospital's rule and permit us to extend our results to the case of the concavity (convexity) with respect to Hölder means. To illustrate the applications of the main results, we discuss in details the geometrical concavity of the probability density function, cumulative distribution function and survival function of some common continuous univariate distributions. Moreover, at the end of the paper, we present a simple alternative proof to Schweizer's problem related to the Mulholland's generalization of Minkowski's inequality.     

Contributions to affine surface area

Representations of equiaffine surface area, due to Leichtweiß resp. Schütt &; Werner, are generalized top-affine surface area measures. We provide a direct proof which shows that these representations coincide. In addition, we establish two theoremes which in particular characterize all those convex bodies geometrically for which the affine surface area is positive. The present approach also leads to proofs of the equiaffine isoperimetric inequality and the Blaschke-Santaló inequality, including the characterization of the case of equality.     

On certain optimization methods with finite-step inner algorithms for convex finite-dimensional problems with inequality constraints

Numerical methods are proposed for solving finite-dimensional convex problems with inequality constraints satisfying the Slater condition. A method based on solving the dual to the original regularized problem is proposed and justified for problems having a strictly uniformly convex sum of the objective function and the constraint functions. Conditions for the convergence of this method are derived, and convergence rate estimates are obtained for convergence with respect to the functional, convergence with respect to the argument to the set of optimizers, and convergence to the g-normal solution. For more general convex finite-dimensional minimization problems with inequality constraints, two methods with finite-step inner algorithms are proposed. The methods are based on the projected gradient and conditional gradient algorithms. The paper is focused on finite-dimensional problems obtained by approximating infinite-dimensional problems, in particular, optimal control problems for systems with lumped or distributed parameters.     

Inequalities on the Triangle

The article deals with generalizations of the inequalities for convex functions on the triangle. The Jensen and the Hermite-Hadamard inequality are included in the study. Considering a convex function on the triangle, we obtain a generalization of the Jensen-Mercer inequality, and a refinement of the Hermite-Hadamard inequality.     

两类Hadamard型不等式的推广

通过引入两个函数,讨论了它们的凸性和单调性,由此得到下凸函数的Hadamard不等式的改进,推广了有关文献的结果.又根据GA-下凸函数与下凸函数的关系,得到GA-凸函数的Hadamard不等式的改进与推广.     

区间上似凸函数的幂平均不等式

定义了区间上似凸函数的概念.利用定积分的性质把凸函数的幂平均不等式Mα(f ) 相似文献   

Remarks on strongly convex functions

Some properties of strongly convex functions are presented. A characterization of pairs of functions that can be separated by a strongly convex function and a Hyers?CUlam stability result for strongly convex functions are given. An integral Jensen-type inequality and a Hermite?CHadamard-type inequality for strongly convex functions are obtained. Finally, a relationship between strong convexity and generalized convexity in the sense of Beckenbach is shown.     

Farkas-type results for inequality systems with composed convex functions via conjugate duality

We present some Farkas-type results for inequality systems involving finitely many functions. Therefore we use a conjugate duality approach applied to an optimization problem with a composed convex objective function and convex inequality constraints. Some recently obtained results are rediscovered as special cases of our main result.     

ε-Optimal solutions in nondifferentiable convex programming and some related questions

In this paper we present ε-optimality conditions of the Kuhn-Tucker type for points which are within ε of being optimal to the problem of minimizing a nondifferentiable convex objective function subject to nondifferentiable convex inequality constraints, linear equality constraints and abstract constraints. Such ε-optimality conditions are of interest for theoretical consideration as well as from the computational point of view. Some illustrative applications are made. Thus we derive an expression for the ε-subdifferential of a general convex ‘max function’. We also show how the ε-optimality conditions given in this paper can be mechanized into a bundle algorithm for solving nondifferentiable convex programming problems with linear inequality constraints.     

Second-order global optimality conditions for convex composite optimization

In recent years second-order sufficient conditions of an isolated local minimizer for convex composite optimization problems have been established. In this paper, second-order optimality conditions are obtained of aglobal minimizer for convex composite problems with a non-finite valued convex function and a twice strictly differentiable function by introducing a generalized representation condition. This result is applied to a minimization problem with a closed convex set constraint which is shown to satisfy the basic constraint qualification. In particular, second-order necessary and sufficient conditions of a solution for a variational inequality problem with convex composite inequality constraints are obtained. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.