贾普利金不等式的转化形式

众所周知,著名的贾普利金微分不等式在求一阶常微分方程的柯西问题的近似积分曲线方面有着广泛的应用.本文将对某些微分方程的离散形式,类似于贾普利金不等式,提出一个代数不等式,然后应用于这些微分方程的数值解法中。     

泰勒公式的应用与技巧

<正> 在高等数学中,有关极值的判定、函数不等式和定积分不等式等问题的证明,往往技巧性很高.通常被人们认为这是数学中的难点,这是因为每个不同的数学问题都具有本身独特的处理方法.由于定积分不等式依赖干函数不等式,而函数不等式的证明方法通常用:拉格朗日中值定理,单调性、函数的极值和凸函数性质等.如何在众多的习题中找到其较好解法.就解题实践而论.对于某些结构特殊的题目,用一般方法求解,求证,常     

某些不等式的极限形式

微积分给证明不等式提供了极其丰富的方法,利用导数、积分及由它们导出的函数的各种性质,使许多用初等方法难以下手的不等式的证明得到容易而迅速的解法。本文从另一角度来考虑,对某些含有n的不等式进行“极限”运算,即把n→∞,看看会得到什么结果和启发。下面我们用两个例子来     

变分不等式的近似解法

Falk曾对凸域和非凸域上的变分不等式问题给出有限元近似解法。特别当区域是非凸时,需要计算很多边界项积分。不管区域是否为凸的情形,本文要给出一个统一的计算格式,此格式不必计算边界项积分,因而可以减少工作量。所得误差也是最优的。     

不等式(组)的解法和证明

Ⅰ不等式的两类基本问题一不等式的解法不等式的解法可分为两大类型题。 (1)代数不等式(组)的解法(包括一元一次不等式(组)、一元二次不等式(组),分式不等式、无理不等式与不等式组、含有绝对值符号的不等式等内容);(Ⅱ)初等超越函数不等式(组)的解法(这里主要是指含有指数函数、对数函数、三角函数的不等式)。下面根据两大类型题的内容顺序以例题形式分述如下。 (1)代数不等式(组)的解法     

应用Cauchy-Schwarz不等式证明积分不等式举例

本文主要以近年大学生数学竞赛的两道典型题目为例,说明Cauchy-Schwarz不等式在证明积分不等式中的应用.这些题目的不同解法既体现了普遍适用性也体现了技巧的针对性,对教师的教学和学生的学习提供帮助.     

追求本质简单自然的数学教学——“一元二次不等式的解法”教学设计与思考

一、课题分析 “一元二次不等式的解法”具有以下三个特点： 1．一元二次不等式的解法是一元一次不等式的解法的延续和深化,它对集合知识起到重要的巩固和运用的作用,也与后继的函数、三角函数、线性规划、直线与圆锥曲线以及导数等内容紧密相关．许多问题的解决都要建立在一元二次不等式正确求解的基础上．可见,一元二次不等式的解法在高中数学中具有极强的基础性和工具性;     

一个特定型定积分不等式的若干推广

通过适当构造辅助函数和应用牛顿—莱布尼兹公式、施瓦兹积分不等式,将一个特定型定积分不等式进行了推广.证明了只要被积函数在积分区间内存在零点,该特定型定积分不等式均成立,进而给出实例说明了该不等式成立的正确性.     

多重的非对称核Hardy-Hilbert积分不等式

该文对Hardy-Hilbert积分不等式进行推广, 建立具有最佳常数因子的非对称核Hardy-Hilbert型积分不等式和加权的Hardy-Hilbert型积分不等式,并考虑它们的一些特殊情况.     

积分不等式证明技巧解析

基于定积分不等式的证明是高等数学教学中的一个难点的认识,重点解析定积分不等式证明过程中所涉及的知识点,并对不等式证明技巧进行分析与归纳,阐述定积分不等式证明的基本思路和解题技巧．     

A CLASS OF REDUCED GRADIENT METHODS FOR HANDLING OPTIMIZATION PROBLEMS WITH LINEAR INEQUALITY CONSTRAINTS

A class of reduced gradient methods for handling general optimization problems with linear equality and inequality constraints is suggested in this paper. Although a slack vector is introduced, the dimension of the problem is not increased, which is unlike the conventional way of transferring the inequality constraints into the equality constraints by introducing slack variables. When an iterate x(k) is not a K-T point of the problem under consideration, different feasible descent directions can be obtained by different choices of the slack vectors. The suggested method is globally convergent and the numerical experiment given in the paper shows that the method is efficient.     

Infinite speed of support propagation for the Derrida–Lebowitz–Speer–Spohn equation and quantum drift–diffusion models

We show that weak solutions of the Derrida–Lebowitz–Speer–Spohn (DLSS) equation display infinite speed of support propagation. We apply our method to the case of the quantum drift–diffusion equation which augments the DLSS equation with a drift term and possibly a second-order diffusion term. The proof is accomplished using weighted entropy estimates, Hardy’s inequality and a family of singular weight functions to derive a differential inequality; the differential inequality shows exponential growth of the weighted entropy, with the growth constant blowing up very fast as the singularity of the weight becomes sharper. To the best of our knowledge, this is the first example of a nonnegativity-preserving higher-order parabolic equation displaying infinite speed of support propagation.     

A linear programming-based optimization algorithm for solving nonlinear programming problems

In this paper a linear programming-based optimization algorithm called the Sequential Cutting Plane algorithm is presented. The main features of the algorithm are described, convergence to a Karush–Kuhn–Tucker stationary point is proved and numerical experience on some well-known test sets is showed. The algorithm is based on an earlier version for convex inequality constrained problems, but here the algorithm is extended to general continuously differentiable nonlinear programming problems containing both nonlinear inequality and equality constraints. A comparison with some existing solvers shows that the algorithm is competitive with these solvers. Thus, this new method based on solving linear programming subproblems is a good alternative method for solving nonlinear programming problems efficiently. The algorithm has been used as a subsolver in a mixed integer nonlinear programming algorithm where the linear problems provide lower bounds on the optimal solutions of the nonlinear programming subproblems in the branch and bound tree for convex, inequality constrained problems.     

Equivalence of the wielandt inequality and the kantorovich inequality

This note shows the equivalence of two well-known inequalities: the Wielandt inequality and the Kantorovich inequality.     

An Affine Scaling Interior Trust Region Method via Optimal Path for Solving Monotone Variational Inequality Problem with Linear Constraints

Based on a differentiable merit function proposed by Taji et al. in ＂Math. Prog. Stud., 58, 1993, 369-383＂, the authors propose an affine scaling interior trust region strategy via optimal path to modify Newton method for the strictly monotone variational inequality problem subject to linear equality and inequality constraints. By using the eigensystem decomposition and affine scaling mapping, the authors form an affine scaling optimal curvilinear path very easily in order to approximately solve the trust region subproblem. Theoretical analysis is given which shows that the proposed algorithm is globally convergent and has a local quadratic convergence rate under some reasonable conditions.     

Local Linear Convergence of an Outer Approximation Projection Method for Variational Inequalities

This paper considers an outer approximation projection method for variational inequalities, in which the projections are not performed on the original set that appears in the variational inequality, but on a polyhedral convex set defined by the linearized constraints. It shows that the method converges linearly, when the starting point is sufficiently close to the solution and the step lengths are sufficiently small.     

Heinz's inequality and Bernstein's inequality

The purpose of the present account is to sharpen Heinz's inequality, and to investigate the equality and the bound of the inequality. As a consequence of this we present a Bernstein type inequality for nonselfadjoint operators. The Heinz inequality can be naturally extended to a more general case, and from which we obtain in particular Bessel's equality and inequality. Finally, Bernstein's inequality is extended to eigenvectors, and shows that the bound of the inequality is preserved.

     

Solvability of the Minty Variational Inequality

We consider the existence of solutions to the Minty variational inequality, as it plays a key role in a projection-type algorithm for solving the variational inequality. It is shown that, if the underlying mapping has a separable structure with each component of the mapping being quasimonotone, then the Minty variational inequality has a solution. An example shows that the underlying mapping itself is not necessarily quasimonotone, although each of its components is.     

Two-level pressure projection finite element methods for Navier-Stokes equations with nonlinear slip boundary conditions

The two-level pressure projection stabilized finite element methods for Navier-Stokes equations with nonlinear slip boundary conditions are investigated in this paper, whose variational formulation is the Navier-Stokes type variational inequality problem of the second kind. Based on the P₁-P₁ triangular element and using the pressure projection stabilized finite element method, we solve a small Navier-Stokes type variational inequality problem on the coarse mesh with mesh size H and solve a large Stokes type variational inequality problem for simple iteration or a large Oseen type variational inequality problem for Oseen iteration on the fine mesh with mesh size h. The error analysis obtained in this paper shows that if h=O(H²), the two-level stabilized methods have the same convergence orders as the usual one-level stabilized finite element methods, which is only solving a large Navier-Stokes type variational inequality problem on the fine mesh. Finally, numerical results are given to verify the theoretical analysis.     

Interior point algorithms for linear programming with inequality constraints

Interior methods for linear programming were designed mainly for problems formulated with equality constraints and non-negative variables. The formulation with inequality constraints has shown to be very convenient for practical implementations, and the translation of methods designed for one formulation into the other is not trivial. This paper relates the geometric features of both representations, shows how to transport data and procedures between them and shows how cones and conical projections can be associated with inequality constraints.