Brown运动的逗留时与首中时

设为中的标准Brown运动,对0＜α,记本文求出了X在首中球面之前逗留在Bα内的时间的Laplace变换,在首中之前逗留在Bαb内的时间的Laplace变换以及在首中之前逗留在Bαb内的时间的Laplace变换．作为推论,求出了X关于球面首中时的Laplace变换,逗留在球内总的时间的Laplace变换及逗留在球壳内的总的时间的LaPlace变换．     

纪念华罗庚教授逝世一周年

华罗庚同志手迹华罗庚同志一九八五年六月十二日在日本东京大学的报告提纲华罗庚教授在数论上的贡献华罗庚教授在代数与几何上的贡献华罗庚教授在多复变函数论上的贡献华罗庚教授在应用数学方面的贡献     

反函数连续性和可微性的若干注记

在不要求函数在区间连续的假设下,研究了其反函数存在的条件及其在一点的连续和可微的条件,给出了反函数在一点连续的本质刻画.主要结论是原函数在某点连续不是其反函数在相应点连续的必要条件,而是函数将区间映射为区间,最后用例子说明结论的直观性.     

Interval DEA模型中决策单元的投影问题

在传统的DEA模型中,最优相对效率模型是在不大于1的范围内研究决策单元的效率的,最差相对效率模型是在不小于1的范围内研究决策单元的效率,这两种模型在研究投影问题时,是在不同的范围内进行的,有一定的片面性.将在interval DEA模型中,研究决策单元的投影问题,该模型是在相同的约束域内研究最优和最差相对效率模型,得出的结论将更加全面,通过两个定理给出了非DEA有效的决策单元在DEA有效面上的投影表达式和非DEA无效的决策单元在DEA无效面上的投影表达式.同时,通过一个实例对决策单元在interval DEA模型中的投影结果与在传统的DEA模型的投影结果进行了比较,发现投影结果比传统模型得到的投影结果对实际的生产有更强的指导意义.     

关于“十字相乘法“是否应保留的一点思考

因式分解本身无论在生活的数学中,还是在理论上的数学中,都不会单独出现,但是因式分解却因为其自身在数学应用中的随处可见性,例如,在求值问题中的运用,在分式运算中的运用,在二次根式计算中的运用,以及在等式、恒等式证明中的运用等等,让它居于一个基础性的地位,属于中学阶段必须要掌握的工具性的数学知识.     

一类具磁场效应的三维非线性Schrdinger方程组的整体解及其渐近性质

§1.引言一类具有磁场效应的Zakharov方程组及其对应的非线性Schrdinger方程组已在[1][2]中提出,并在物理上进行了研究.在[3]中,我们从数学上证明了该方程组在R~2空间上解的存在性.在[4]中,我们研究了它的初边值问题在     

浅谈高中数学的类比方法

世界万物总在不断变化、完善着,数学知识亦不例外.对诸多数学知识的理解在深化,应用在优化,有诸多数学命题在延伸、拓广,在这些变化过程中“类比”有着它独特的功效.     

摆线教学中的一个问题

在讨论摆线的时候,常常要涉及到一个圆在一条直线或一条曲线上的滚动.我们知道,圆可以在一条直线上滚动,圆也可以在另一个圆的外面保持相切而滚动,但一个圆未必一定能在另一个圆的内部保持相切而滚动,又例如单位圆就不能在抛物线y=x~2的     

几何画板在初中几何教学中的运用

以前的课堂,人们总是把黑板、粉笔或纸笔联系在一起,这样的教学方式会把学生的思维局限在有限的空间中.在科学技术高度发展的今天,多媒体的应用已经相当普及,尤其是在教师开课的时候基本上都有精美课件的展示.在数学课上,几何画板的运     

渐进二次泛函在无穷远处的临界群

在Bartsch-Li建立的在无穷远处的分裂定理的基础上，证明一个关于渐近二次泛函在无穷远处的临界群的计算的结果，它类似于泛函在孤立临界点处的临界群的相应结果。     

Frame expansions for Gabor multipliers

Discrete Gabor multipliers are composed of rank one operators. We shall prove, in the case of rank one projection operators, that the generating operators for such multipliers are either Riesz bases (exact frames) or not frames for their closed linear spans. The same dichotomy conclusion is valid for general rank one operators under mild and natural conditions. This is relevant since discrete Gabor multipliers have an emerging role in communications, radar, and waveform design, where redundant frame decompositions are increasingly applicable.     

Asymptotics of the discrete spectrum of a perturbed Hill operator

One considers a perturbed one-dimensional Hill operator. One gives a formula for the asymptotics of the discrete spectrum in the gap of the continuous spectrum and conditions under which this formula is valid.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 147, pp. 188–189, 1985.In conclusion the author expresses his deep gratitude to his scientific adviser M. Sh. Birman for the formulation of the problem and for his constant interest in this note.     

Application of a Near-Optimal Reinforcement Learning Controller to a Robotics Problem in Manufacturing: A Hybrid Approach

Optimization theory provides a framework for determining the best decisions or actions with respect to some mathematical model of a process. This paper focuses on learning to act in a near-optimal manner through reinforcement learning for problems that either have no model or the model is too complex. One approach to solving this class of problems is via approximate dynamic programming. The application of these methods are established primarily for the case of discrete state and action spaces. In this paper we develop efficient methods of learning which act in complex systems with continuous state and action spaces. Monte-Carlo approaches are employed to estimate function values in an iterative, incremental procedure. Derivative-free line search methods are used to obtain a near-optimal action in the continuous action space for a discrete subset of the state space. This near-optimal control policy is then extended to the entire continuous state space via a fuzzy additive model. To compensate for approximation errors, a modified procedure for perturbing the generated control policy is developed. Convergence results under moderate assumptions and stopping criteria are established.     

Numerical analysis and algorithms in control and state constrained optimization with PDEs

We consider an elliptic optimal control problem with control and pointwise state constraints. The cost functional is approximated by a sequence of functionals which are obtained by discretizing the state equation with the help of linear finite elements and enforcing the state constraints in the nodes of the triangulation. The control variable is not discretized. A general error bound for control and state is obtained which forms the starting point for optimal error estimates in both in two and three space dimensions. For the numerical implementation of the discrete concept fix-point iterations or generalized Newton methods are proposed. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Some practical stability criteria for systems of linear differential equations

We examine some problems of practical stability of motion of linear systems when the initial state of the phase trajectory is contained in a ball in the l_p space. Various constraints on the phase state are considered. Parametric stability criteria and stability criteria under simultaneous constraints on the initial state and the perturbations are derived.Translated from Vychislitel'naya i Prikladnaya Matematika, No. 62, pp. 99–104, 1987.     

Semidefinite relaxations of dynamical programs under discrete constraints

In this work we propose an exact semidefinite relaxation for non-linear, non-convex dynamical programs under discrete constraints in the state variables and the control variables. We outline some theoretical features of the method and workout the solutions of a benchmark problem in cybernetics and the classical inventory problem under discrete constraints.     

On inf-sup conditions and projections in the theory of mixed finite-element methods

We indicate constraints on the space of finite elements providing the validity of discrete inf-sup conditions and the existence of projections specific for mixed finite-element methods. We consider both conformal and nonconformal approximations. We suggest a definition of special projections onto the vector space of finite elements which provides their existence under quite general conditions without determining the degrees of freedom of the elements.     

A Variational Discretization Concept in Control Constrained Optimization: The Linear-Quadratic Case

A new discretization concept for optimal control problems with control constraints is introduced which utilizes for the discretization of the control variable the relation between adjoint state and control. Its key feature is not to discretize the space of admissible controls but to implicitly utilize the first order optimality conditions and the discretization of the state and adjoint equations for the discretization of the control. For discrete controls obtained in this way an optimal error estimate is proved. The application to control of elliptic equations is discussed. Finally it is shown that the new concept is numerically implementable with only slight increase in program management. A numerical test confirms the theoretical investigations.     

Superconvergence analysis of fully discrete finite element methods for semilinear parabolic optimal control problems

We study the superconvergence property of fully discrete finite element approximation for quadratic optimal control problems governed by semilinear parabolic equations with control constraints. The time discretization is based on difference methods, whereas the space discretization is done using finite element methods. The state and the adjoint state are approximated by piecewise linear functions and the control is approximated by piecewise constant functions. First, we define a fully discrete finite element approximation scheme for the semilinear parabolic control problem. Second, we derive the superconvergence properties for the control, the state and the adjoint state. Finally, we do some numerical experiments for illustrating our theoretical results.     

A Learning Algorithm for the Control of Continuous Action Set-Point Regulator Systems

The convergence properties for reinforcement learning approaches, such as temporal differences and Q-learning, have been established under moderate assumptions for discrete state and action spaces. In practice, however, many systems have either continuous action spaces or a large number of discrete elements. This paper presents an approximate dynamic programming approach to reinforcement learning for continuous action set-point regulator problems, which learns near-optimal control policies based on scalar performance measures. The continuous-action space (CAS) algorithm uses derivative-free line search methods to obtain the optimal action in the continuous space. The theoretical convergence properties of the algorithm are presented. Several heuristic stopping criteria are investigated and practical application is illustrated by two example problems—the inverted pendulum balancing problem and the power system stabilization problem.