分段函数问题的类型及解法

分段函数由于是分段定义的 ,在不同的区间上函数有着不同的对应法则 ,与一般函数有着明显的区别 .学生往往受负迁移影响对分段函数问题认识不清或思维片面产生解题错误 ,本文就分段函数问题的类型进行归类解析 .1　判定分段函数的奇偶性例 1　判定分段函数f (x) =(110 ) x,x >0     

分段函数的三点注解

<正>分段函数是一类常见的函数,也是高考中函数考查的重点.相对于只有一个解析式的函数,分段函数的形式显得复杂些,同学们在求解分段函数问题时,也更易出现失误.因此,分段函数的学习又是一个难点.对于分段函数的学习,首先要重视正确理解概念,其次要准确把握性质特征,最后要注意揭示问题内隐.     

探析分段函数问题

<正>1问题提出分段函数指的是一种在定义域的不同部分有着不同的对应关系的函数,其本质是一个函数.最简单的问题莫过于分段函数的求值问题,解决此问题关键是弄清自变量属于分段函数的哪一段.更复杂的是以分段函数为载体,考查最值、单调性、零点、方程、不等式等问题,其中最为常见的是含参数的问题.在处理含参问题时往往会犯这样那样的错误,如分类讨论不完整、问题不能准确转化等.本文通过一系列的例子来专门探析分析函数常考查的主要问题.     

分段函数在分段点处可导性的判别方法

针对高等数学课程中分段函数可导性问题,基于函数可微的概念和泰勒公式给出一种新的分段函数在分段点处可导性的判别方法.该方法不需按照导数定义计算分段点处的导数,也不需求导函数在分段点处的极限.与它们相比,该方法更简单,同时加深了对可微概念的理解.     

分段函数——高考数学新视点

分段函数问题近年在高考试题中频繁出现 ,业已成为高考数学的一个热点 .但现行教材与复习资料对这类问题尚无系统介绍 ,现对其做一归纳整理 ,供同学们复习时参考 .1　分段函数的概念定义　一个函数在它的定义域中 ,对于自变量x的不同取值范围 ,对应法则不同 ,这样的函数叫做分段函数 .由定义可知 ,分段函数是“一个”函数 ,而不是几个函数 ,它是由各段上的解析式 (对应法则 )用符号“{”合并而成的一个整体 ,其定义域是各段自变量集合的并集 ,值域是各段函数值集合的并集 .2　分段函数考题的类型2 .1　分段函数的解析式 .例 1　 (2 0 0 0年…     

高考数学题中的分段函数

<正>分段函数是高中数学的重要内容,它能有效考察函数的概念,性质及图像,因而在近几年高考中倍受青睐,特别是以分段函数为背景的问题常考常新.本文就高考中分段函数的若干种题型及其解法作以探讨,供大家参考.类型1已知分段函数求函数值     

多维正态分布函数的表示

在许多金融问题的研究中,如金融衍生产品定价、金融风险度量与管理等领域,经常用到多维正态分布函数.在概率论与数理统计文献中只给出了一维标准正态分布表,而多维正态分布函数的计算问题没有给出具体的算法.本文给出了多维正态分布函数与一维标准正态分布函数的关系式,从而解决了多维正态分布函数的计算问题.     

示性函数在初等概率论中的应用

示性函数在实分析等课程中很基本且应用广泛,但在初等概率论教材里应用不多.本文举例说明示性函数可以帮助学生理解初等概率论中一些基本概念、结论并精简其中一些计算.     

分段函数的研究性学习

分段函数是指自变量在不同取值范围,对应法则不同的函数,分段函数是一个整体,分段函数的定义域是各段定义域的并集.自Euler和Larange允许不同定义区域可以具有不同的表达式以来,就一直活跃在分析学领域,其中,连续与间断的问题的表达,连续点不可导的反例,以及L-积分与R-积分的分水岭,都是由分段函数给出的.     

例谈分段函数在高考中的四个考查方向

分段函数是高中数学中一类重要的函数类型,不仅能考查函数的概念、表示及性质,而且能有效考查学生数学思想方法,因此在高考中被频繁考查.下面,从四个方面说明分段函数在高考中的考查方向. 一、对应性 与分段函数相关的函数值、方程、不等式问题,由于自变量的取值范围不同,对应法则不同,应根据定义域分类讨论.分段函数在高考中首先考查对应性,由于对应的不确定,实质考查分类讨论思想.     

An uncertainty interchange format with imprecise probabilities

This paper addresses the problem of exchanging uncertainty assessments in multi-agent systems. Since it is assumed that each agent might completely ignore the internal representation of its partners, a common interchange format is needed. We analyze the case of an interchange format defined by means of imprecise probabilities, pointing out the reasons of this choice. A core problem with the interchange format concerns transformations from imprecise probabilities into other formalisms (in particular, precise probabilities, possibilities, belief functions). We discuss this so far little investigated question, analyzing how previous proposals, mostly regarding special instances of imprecise probabilities, would fit into this problem. We then propose some general transformation procedures, which take also account of the fact that information can be partial, i.e. may concern an arbitrary (finite) set of events.     

n元随机变量联合分布的分解

定义和研究了函数Sum(n,t),并借助于此以模n剩余类环上函数的频谱理论为工具解决了n元随机变量联合分布的分解问题。     

On weak convergence of random fields

We provide a characterization of compactness in the spaceD of functions of two variables defined on a unit square. The functions fromD have the property that their discontinuity points lie on smooth curves. Conditions for the tightness of probability measures inD and conditions for weak convergence of random fields with trajectories inD are derived. Vilnius Gediminas Technical University, Saulétekio 11; Institute of Mathematics and Informatics, Akademijos 4, 2600 Vilnius, Lithuania. Translated from Lietuvos Matematikos Rinkinys, Vol. 39, No. 2, pp 169–184, April–June, 1999. Translated by R. Banys     

An analogue of Hunt's representation theorem in quantum probability

In quantum mechanics certain operator-valued measures are introduced, called instruments, which are an analogue of the probability measures of classical probability theory. As in the classical case, it is interesting to study convolution semigroups of, instruments on groups and the associated semigroups of probability operators, which now are defined on spaces of functions with values in a von Neumann algebra. We consider a semigroup of probability operators with a continuity property weaker than uniform continuity, and we succeed in characterizing its infinitesimal generator under the additional hypothesis that twice differentiable functions belong to the domain of the generator. Such hypothesis can be proved in some particular cases. In this way a partial quantum analogue of Hunt's representation theorem for the generator of convolution semigroups on Lie groups is obtained. Our result provides also a closed characterization of generators of a new class of not norm continuous quantum dynamical semigroups.     

Imprecise set and fuzzy valued probability

Set valued probability and fuzzy valued probability theory is used for analyzing and modeling highly uncertain probability systems. In this paper the set valued probability and fuzzy valued probability are defined over the measurable space. They are derived from a set and fuzzy valued measure using restricted arithmetics. The range of set valued probability is the set of subsets of the unit interval and the range of fuzzy valued probability is the set of fuzzy sets of the unit interval. The expectation with respect to set valued and fuzzy valued probability is defined and some properties are discussed. Also, the fuzzy model is applied to binomial model for the price of a risky security.     

完全区间树顶点数目的大数律

本文讨论完全区间树顶点数目Sx的大数律,所采用的方法不同于单边区间树．文章包括三部分内容:首先探讨完全区间树所得以定义的概率空间,弄清楚它的结构,为强大数律的研究奠定理论基础．接着,针对完全区间树上的Sx的矩母函数不易求得的情况,另辟蹊径,求得Sx的期望和方差．最后,给出Sx的强弱大数律．     

竞争型二元风险模型破产概率

本文研究了竞争型的二元风险模型,定义了两类破产概率以及状态过程,利用经典风险模型的已有结果和条件期望的性质,得到两类破产概率表达式,以及单个保险公司有限时间破产概率和最终破产概率,并给出两个保险公司的状态过程的概率分布列.     

Probability of fuzzy events defined as denumerable additivity measure

In this paper the probability of fuzzy events is defined as a denumerable additivity measure. This definition is based on a non-conventional approach of separativity between fuzzy subsets. The presented measure fulfils all properties analogous to the properties of classical probability in the crisp case. Further, the notion of conditional probability of fuzzy events, complete fuzzy repartition and independent fuzzy events are defined by means of the probability measure considered here. Connections between all the above notions are presented in this paper, too. Finally, the Bayes formula is proved for the fuzzy case.