连续函数压缩映射问题的讨论

就连续函数应用问题的教学内容进行探讨.介绍数列和连续函数的压缩映射原理及其在方程求解,数学建模等方面的应用,并给出压缩映射的一般形式.续而通过压缩映射原理在图像处理和导航系统中的应用,阐明创新思想的重要性,以求开拓学生的思路和想象空间.     

一个水平集为完备集的连续函数的解析构造

本文给出一个水平集是完备集的连续函数的解析表达．     

借助函数极限判断无限数列的敛散性

本文首先指出了什么是无限数列和无限数列的敛散性的特征,数列的敛散性和连续函数的极限的求值有怎样的关系?数列的敛散性必有其特殊的地方,同时,将连续函数的求极限的方法移植到数列敛散性的判别上,有哪些需要注意的地方.文中作者将针对两者关系进行了详细的论述.无限数列在无穷远处的项具有什么特点呢?或是渐近某一个数,或渐近某几个数,或在某几个数之间来回摇摆等等.当数列渐近某一个数时,无限数列收敛.无限数列敛散性的代数验证方法就是求其在无穷远处的极限.当极限结果为一个有限数时,无穷数列收敛,当极限结果为无穷或不存在时,称其发散.既然数列是一种特殊的函数,那么是否可以借助函数极限来求解数列的极限呢?     

凸函数与半连续函数的关系

通过研究凸函数与半连续函数的关系,给出了凸函数的一个与上半连续性相结合的等价定义.     

一收敛数列的极限

给出了求数列{xn}:xn=sin1/2 sin2/2^2 ……sinn/2^n的极限的一种方法,并求出了该极限。     

关于半连续函数与凸函数的注记

在半连续前提下,给出凸函数和严格凸函数的不等式刻划．指出非空凸集上的半连续函数满足中间点凸性时,成为凸函数,满足中间点严格凸性时,成为严格凸函数．最后定义F—G广义凸函数和条件p1,p2等概念,列举若干满足条件p1,p2的数量函数和向量函数,并指出,对于F—G广义凸函数,在条件p1,p2及一定连续性条件下,可以得到类似结果．     

一道数列极限的多种解法

利用数学分析中关于数列极限的定义、收敛数列的性质及数列极限存在的条件,介绍一道数列极限问题的多种解法.     

关于模糊数列收敛问题的注记

分析模糊数列收敛极限的几种定义．指出一些文献中的不当．研究它们的关系，讨论一类模糊数拓扑线性空间。     

一类递推型数列收敛的充要条件

证明了 :设c>1 ,{bn}是正数列 ,令an=cb1+cb2 +… +cbn,n =1 ,2 ,… ,则 {an}收敛的充要条件是数列 lnbncn 有上界。     

Description of Closed Maximal Ideals in Topological Algebras of Continuous Vector-Valued Functions

Let X be a completely regular Hausdorff space, A be a unital locally convex algebra with jointly continuous multiplication and C(X,A) be the algebra of all continuous A-valued functions on X equipped with the topology of \({\mathcal{K}(X)}\) -convergence. Moreover, let \({\mathfrak{M}_{\ell}(A)}\) and \({\mathfrak{M}(A)}\) denote the set of all closed maximal left and two-sided ideals in A, respectively. In this note, we describe all closed maximal left and two-sided ideals in C(X,A) and show that there exist bijections from \({\mathfrak{M}_{\ell}(C(X, A))}\) onto \({X \times \mathfrak{M}_{\ell}(A)}\) and \({\mathfrak{M}(C(X, A))}\) onto \({X \times \mathfrak{M}(A)}\) . We also present new characterizations of closed maximal ideals in C(X, A) when A is a unital commutative locally convex Gelfand–Mazur algebra with jointly continuous multiplication.     

Inverse Problems of Submodular Functions on Digraphs

In this paper, we study the inverse problem of submodular functions on digraphs. Given a feasible solution x* for a linear program generated by a submodular function defined on digraphs, we try to modify the coefficient vector c of the objective function, optimally and within bounds, such that x* becomes an optimal solution of the linear program. It is shown that the problem can be formulated as a combinatorial linear program and can be transformed further into a minimum cost circulation problem. Hence, it can be solved in strongly polynomial time. We also give a necessary and sufficient condition for the feasibility of the problem. Finally, we extend the discussion to the version of the inverse problem with multiple feasible solutions.     

Inverse Functions of Number-Theoretic Functions (I)

If gf(x) =x for every x, then g is called a left inverse function of f and f is a right inverse function of g. If f is both left and right inverse function of g, then f and g are said to be mutually inverse to each other. We show that (§ 1) the following results hold. A function f has a left inverse if and only if f is univalent, a function g has a right inverse if and only if g is exhaustive, i. e., g takes every (natural) number as values. Hence f has both left and right inverse if and only if f is both univalent and exhaustive, i. e., f is a permutation on the domain of natural numbers. Let g_1 and g_2 be two left inverse functions of the function f. If for every left inverse g of f, we have $g_1(x) \leq g(x) \leq g_2(x)$, then g_1(x) is called the weak, and g_2(x) is the strong, left inverse function of f. Similarly we define the weak and the strong right inverse functions. We show that(§ 2) every strict increasing function f must possess weak and strong left inverse functions, and all of its left inverse functions must be exhaustive slow increasing (a function g(x) is slow increasing if and only if g(Sx) —Sg(x) =0, here s denotes the successor function). On the other hand, every exhaustive function g must possess weak and strong right inverse functions, and all of its right inverse functions must strict increasing. We show also that (§ 3): If f_1(x) and f_2(x) both take g(x) as their strong (weak) left inverse, then f_1(x)=f_2(x)(f_1(Sx)=f_2(Sx)). If g_1(x) and g_2(x) both take f(x) as their strong or weak right inverse, then g_1(x)=g_2(x). From these results we see that we may find a function from its strong (weak) left or right inverse function. Let there be f(c) \leq x 相似文献   

关于弱收敛非负随机变量序列的逆矩

在2 δ阶矩有限时,对一类非负弱收敛随机变量列,给出了成立的充分条件,推广了[2]中的结果并严密了其中主要结果定理3,定理4的证明．     

Well-positioned Closed Convex Sets and Well-positioned Closed Convex Functions

We characterize the class of those closed convex sets which have a barrier cone with a nonempty interior. As a consequence, we describe the set of those proper extended-real-valued functionals for which the domain of their Fenchel conjugate has a nonempty interior. As an application, we study the stability of the solution set of a semi-coercive variational inequality.     

无穷限反常积分收敛时被积函数的极限状态

根据无穷限反常积分∫a^＋∞f（x）dx收敛的柯西准则和定积分的性质,讨论被积函数f（x）当x→∞时。的极限状态,并得出当无穷限反常积分∫a^＋∞f（x）dx收敛且f（x）在[a,＋∞）上连续,或者无穷限反常积分∫a^＋∞f（x）dx绝对收敛时,存在数列{xn}∩[a,＋∞]且xn→＋∞（n→∞）,使limn→∞xnf（xn）=0.     

Limit Superior of Subdifferentials of Uniformly Convergent Functions

In this paper we show that the – subdifferential of a lower semicontinuous function is contained in the limit superior of the – subdifferential of lower semicontinuous uniformly convergent family to this function. It happens that this result is equivalent to the corresponding normal cones formulas for family of sets which converges in the sense of the bounded Hausdorff distance. These results extend to the infinite dimensional case those of Ioffe for – functions and of Benoist for Clarkes normal cone. As an application we characterize the subdifferential of any function which is bounded from below by a negative quadratic form in terms of its Moreau–Yosida proximal approximation.