对称性在微积分中的一些应用

对称的概念在数学领域有着非常广泛而重要的作用,人们可以利用问题涉及的数学对象本身具有的对称因素去解决问题,在微积分部分,利用函数,积分域等所具有的对称性可以拓展思路,简化运算,下面举例说明,仅供教学中参考．一、在微分计算中的应用定义1若将n元函数中任意两个变元对换而函数不变,则称是对称函数．规则是偏导数存在的对称。数,则具,中的X换成y,y换成X,就得到了．规则1可以推广到任意n元对称函数中每一个变元的任意m阶偏导数．利用函数X的对称性,将（1）、（2）式中X,y互换得将（1）、（2）式中工,Z互换得定义2如果…     

一道导数题的求证感悟

评注 学生思路直接易想,将函数极小值转化为关于a的函数,但运算超出学生能力范围,导致无为之错．参考解答,另辟蹊径,将a换成x2,将x2视为主元,构造新函数,其中x2〉1是关键．     

关于混合插值样条

本文中我们提出一类特殊的H-B插值问题,即所谓混合插值.我们首先讨论五次样条,它是将Meir和Sharma的缺插值样条中的二阶导数的逐点插值换成一阶导数与二阶导数的交替插值.然后又讨论了三次样条,将[3]中讨论的(p)型插值改成一阶导数及函数值本身在节点处的交替插值.我们研究了这两类样条的存在、唯一性,并得到了它     

广义模糊DEA模型及其有效性研究

考虑到样本单元和待评价决策单元输入输出数据的模糊性,提出了广义模糊DEA模型,利用α-截集,将广义模糊DEA变换成以置信水平α为参数的参数规划,给出了待评价决策单元效率值θ~*的效率区间的计算方法,并在此基础上讨论了θ~*的隶属函数μ_(θ*).     

基于B样条的函数型数据表示与配准

针对函数型数据配准问题,首先利用B样条函数来近似表示,并将扭曲函数也限定为于B样条函数空间内.进而将函数型数据配准问题转换为B样条函数升阶后比较控制顶点的问题,可降低计算复杂度.数值实验验证了该方法的有效性.     

第一类振荡积分的推广及其估计

研究经典的第一类振荡积分的推广,即将经典的第一类振荡积分中的指数函数换成满足某个线性微分方程的实函数后所对应的振荡积分I(λ).首先讨论I(λ)的局部性质,即I(λ)随λ的变化情况(限定λ0);其次给出当相位函数φ(x)满足|φ~((k))(x)|≥1时,I(λ)的一个大小估计.     

二项线性随机效应模型的拟蒙特卡罗估计

讨论了如何运用拟蒙特卡罗方法对二项线性随机效应模型进行参数估计.首先写出观测数据的边缘对数似然函数,然后用拟蒙特卡罗方法将函数中的积分写成求和的形式,接着利用Newton-Raphson算法计算参数的极大似然估计.以一组种子数据为例,说明该方法是简单可行的.     

智慧窗

1恭贺新年将下列算式中的汉字换成“0 ,1,2 ,… ,9”这十个数字 ,使算式成立编 +辑 =部向 -作 =者恭×贺 =新年江西赣县田村中学 ( 34 110 2 )　刘延炳2万事如意下图是含年号 2 0 0 3的结构图 ,请你将图中的汉字分别换成 1到 10这十个数字 ,使图中的每个棱形的四个角上的四个数字之和都等于 18.安徽淮南三中 ( 2 32 0 0 7)　王秉春3刊名趣题请找出使下列等式成立的数字算式 .中学 =3 生数学北大附中河南分校 ( 451171)张丕臣4巧换数字将下列两个算式中的汉字换成小于 5 0的不同的自然数 ,使等式成立 .中2 +学2 +生2 +数2 +学2 +真2 +诚2 =2 …     

智慧窗

1贺三十周年今年是本刊创立三十周年,为此,下面特拟出一组有关趣题,向贵刊祝贺.1.将下述算式中的汉字换成从小到大、且在30以内的自然数,使算式成立.     

建立等式

下述是《红楼梦》第十八回中,林黛玉作"杏帘在望"中的后面四句,请你将各句中的汉字分别换成 1 ～19( 含 1、19) 以内、且不相同的整数,使等式成立.     

Global robust stability for stochastic interval neural networks with continuously distributed delays of neutral type

In this paper, by using the Lyapunov-Krasovskii functional method, we investigate the global robust stability for stochastic interval neural networks with continuously distributed delays of neutral type. Some new stability criteria are presented in terms of linear matrix inequality (LMI). Two numerical examples are also given to show the effectiveness of the obtained results using LMI control toolbox in MATLAB.     

On the Construction of Optimal Monotone Cubic Spline Interpolations

In this paper we derive necessary optimality conditions for an interpolating spline function which minimizes the Holladay approximation of the energy functional and which stays monotone if the given interpolation data are monotone. To this end optimal control theory for state-restricted optimal control problems is applied. The necessary conditions yield a complete characterization of the optimal spline. In the case of two or three interpolation knots, which we call thelocalcase, the optimality conditions are treated analytically. They reduce to polynomial equations which can very easily be solved numerically. These results are used for the construction of a numerical algorithm for the optimal monotone spline in the general (global) case via Newton's method. Here, the local optimal spline serves as a favourable initial estimation for the additional grid points of the optimal spline. Some numerical examples are presented which are constructed by FORTRAN and MATLAB programs.     

Global asymptotic stability of stochastic reaction-diffusion neural networks with time delays in the leakage terms

In this paper, a class of stochastic reaction-diffusion neural networks with time delays in the leakage terms is investigated. By using the Lyapunov functional method and linear matrix inequality (LMI) approach, sufficient conditions are derived to ensure the global asymptotic stability of an equilibrium point of the networks in the mean square. The results can be easily solved by MATLAB LMI toolbox. Finally, a numerical example is given to demonstrate the effectiveness and conservativeness of our theoretical results.     

Numerical implementation of iteration processes applied in the study of nonlinear boundary value problems of the theory of elasticity and filtration

Nonlinear elastic problems for hardening media are solved by applying the universal iteration process proposed by A.I. Koshelev in his works on the regularity of solutions to quasilinear elliptic and parabolic systems. This requires numerically solving a linear elliptic system at each step of the iteration procedure. The method is numerically implemented in the MATLAB environment by using its PDE Toolbox. A modification of the finite-element procedure is suggested in order to solve a linear algebraic system at each iteration step. The computer model is tested on simple examples. The same nonlinear problems are also solved by the method of elastic solutions, which consists in replacing the Laplace operator in the universal iteration process by the Lamé operator of linear elasticity. As is known, this iteration process converges to a weak solution of the nonlinear problem, provided that the displacements are fixed on the boundary. The method is tested on examples with stresses on the boundary. The third part of the paper is devoted to the nonlinear filtration problem. General properties of the iteration process for nonlinear parabolic systems have been studied by A.I. Koshelev and V.M. Chistyakov. The numerical implementation is based on slightly modified PDE Toolbox procedures. The program is tested on simple examples.     

LMI conditions for stability of impulsive stochastic Cohen–Grossberg neural networks with mixed delays

In this paper, the global asymptotic stability of impulsive stochastic Cohen–Grossberg neural networks with mixed delays is investigated by using Lyapunov–Krasovskii functional method and the linear matrix inequality (LMI) technique. The mixed time delays comprise both the multiple time-varying and continuously distributed delays. Some new sufficient conditions are obtained to guarantee the global asymptotic stability of the addressed model in the stochastic sense using the powerful MATLAB LMI toolbox. The results extend and improve the earlier publications. Two numerical examples are given to illustrate the effectiveness of our results.     

Impulsive controller design for exponential synchronization of chaotic neural networks with mixed delays

This paper considers the chaotic synchronization problem of neural networks with time-varying and distributed delays using impulsive control method. By utilizing the stability theory for impulsive functional differential equations, several impulsive control laws are derived to guarantee the exponential synchronization of neural networks with time-varying and distributed delays. It is shown that chaotic synchronization of the networks is heavily dependent on the designed impulsive controllers. Moreover, these conditions are expressed in terms of LMI and can be easily checked by MATLAB LMI toolbox. Finally, a numerical example and its simulation are given to show the effectiveness and advantage of the proposed control schemes.     

极值理论在高频数据中的VaR和CVaR风险价值研究

高频数据具有与低频数据明显不同的特征。本文引入广义帕雷托分布代替传统的正态分布等,精确描述金融高频数据收益的厚尾特征;并且计算高频数据下的VaR和CVaR,然后利用深成A指数据进行返回检验。两种返回检验方法的结果表明,极值理论方法可以比较精确地度量VaR和CVaR。     

Generalized Lyapunov functions and functional equations

Summary Some results of Minty and Browder on the existence of solutions of functional equations are generalized by replacing the notion of monotony by one involving a Lyapunov function. In the last section, analogous arguments are used to obtain an existence theorem for an initial value problem belonging to an ordinary differential equation on Hilbert space. This work was supported by Air Force Office of Scientific Research.     

Fuzzy qualitative trigonometry

This paper presents a fuzzy qualitative representation of conventional trigonometry with the goal of bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in the domain of physical systems, especially in intelligent robotics. Fuzzy qualitative coordinates are defined by replacing a unit circle with a fuzzy qualitative circle; a Cartesian translation and orientation are defined by their normalized fuzzy partitions. Conventional trigonometric functions, rules and the extensions to triangles in Euclidean space are converted into their counterparts in fuzzy qualitative coordinates using fuzzy logic and qualitative reasoning techniques. This approach provides a promising representation transformation interface to analyze general trigonometry-related physical systems from an artificial intelligence perspective.Fuzzy qualitative trigonometry has been implemented as a MATLAB toolbox named XTRIG in terms of 4-tuple fuzzy numbers. Examples are given throughout the paper to demonstrate the characteristics of fuzzy qualitative trigonometry. One of the examples focuses on robot kinematics and also explains how contributions could be made by fuzzy qualitative trigonometry to the intelligent connection of low-level sensing & control tasks to high-level cognitive tasks.     

Fuzzy qualitative trigonometry

This paper presents a fuzzy qualitative representation of conventional trigonometry with the goal of bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in the domain of physical systems, especially in intelligent robotics. Fuzzy qualitative coordinates are defined by replacing a unit circle with a fuzzy qualitative circle; a Cartesian translation and orientation are defined by their normalized fuzzy partitions. Conventional trigonometric functions, rules and the extensions to triangles in Euclidean space are converted into their counterparts in fuzzy qualitative coordinates using fuzzy logic and qualitative reasoning techniques. This approach provides a promising representation transformation interface to analyze general trigonometry-related physical systems from an artificial intelligence perspective.Fuzzy qualitative trigonometry has been implemented as a MATLAB toolbox named XTRIG in terms of 4-tuple fuzzy numbers. Examples are given throughout the paper to demonstrate the characteristics of fuzzy qualitative trigonometry. One of the examples focuses on robot kinematics and also explains how contributions could be made by fuzzy qualitative trigonometry to the intelligent connection of low-level sensing & control tasks to high-level cognitive tasks.