一类二分图的k-匹配数

设G是一个具有二分类(X_1,X_2)的简单偶图,|X_1|=|X_2|=n,如果对于给定的c>0,|M(S)|≥(1+c)|S|对任意满足|S|≤n/2的S(?)X_i(i=1,2)都成立,其中N(S)是S的邻集,则称G是(n,c)-扩张图.给出了(n,c)-扩张图的k-匹配数与完美匹配数之比的顺从界.     

A Uniaxial Optimal Perfectly Matched Layer Method for Time-harmonic Scattering Problems

We develop a uniaxial optimal perfectly matched layer （opt PML） method for solving the time-harmonic scattering problems by choosing a particular absorbing function with unbounded integral in a rectangular domain. With this choice, the solution of the optimal PML problem not only converges exponentially to the solution of the original scatting problem, but also is insensitive to the thickness of the PML layer for sufficiently small parameter ε0. Numerical experiments are included to illustrate the competitive behavior of the proposed optimal method.     

一类新图的匹配唯一性

利用图的匹配多项式及其最大实数根的性质证明了树T(1,1,n,2,1)及补图匹配唯一的充要条件是n≠1,2,5,8.     

吸收边界条件和完美匹配层

证明了一个Maxwell方程的完美匹配层的的充要条件.条件的核心是吸收边界条件.这个判据可以用来检验文献中的各个模型,也可用来设计一些新的模型.最后给出了一些例子.     

吸收边界条件和完美匹配层

证明了一个Maxwell方程的完美匹配层的的充要条件.条件的核心是吸收边界条件.这个判据可以用来检验文献中的各个模型,也可用来设计一些新的模型.最后给出了一些例子.     

Uniform Convergence Analysis of Finite Difference Scheme for Singularly Perturbed Delay Differential Equation on an Adaptively Generated Grid

<正>Adaptive grid methods are established as valuable computational technique in approximating effectively the solutions of problems with boundary or interior layers. In this paper,we present the analysis of an upwind scheme for singularly perturbed differential-difference equation on a grid which is formed by equidistributing arc-length monitor function.It is shown that the discrete solution obtained converges uniformly with respect to the perturbation parameter.Numerical experiments illustrate in practice the result of convergence proved theoretically.     

The effect of variable viscosity on MHD viscoelastic fluid flow and heat transfer over a stretching sheet

An analysis has been carried out to study the momentum and heat transfer characteristics in an incompressible electrically conducting non-Newtonian boundary layer flow of a viscoelastic fluid over a stretching sheet. The partial differential equations governing the flow and heat transfer characteristics are converted into highly non-linear coupled ordinary differential equations by similarity transformations. The effect of variable fluid viscosity, Magnetic parameter, Prandtl number, variable thermal conductivity, heat source/sink parameter and thermal radiation parameter are analyzed for velocity, temperature fields, and wall temperature gradient. The resultant coupled highly non-linear ordinary differential equations are solved numerically by employing a shooting technique with fourth order Runge–Kutta integration scheme. The fluid viscosity and thermal conductivity, respectively, assumed to vary as an inverse and linear function of temperature. The analysis reveals that the wall temperature profile decreases significantly due to increase in magnetic field parameter. Further, it is noticed that the skin friction of the sheet decreases due to increase in the Magnetic parameter of the flow characteristics.     

利用B样条曲线设计指纹图像滤波模板和快速指纹特征匹配算法

在指纹图像识别过程中,指纹图像的滤波去噪音二值化和指纹特征的匹配是最关键的两个部分.本文针对这两部分的算法设计进行分析和改进,介绍利用B样条造型来设计指纹滤波模板的方法和基于基准点附近的拓扑结构进行快速特征匹配的算法.并且利用改进后的指纹特征匹配算法,在样本指纹库中进行实验,结果表明该算法大大提高了指纹特征匹配的效率和准确性.     

不确定偏好序下的双边匹配博弈

针对带有不确定偏好序的双边匹配问题,现有方法大都仅注重整体收益之和,忽略了参与人的个体收益以及在交互选择中的策略运用.基于最大满意度准则,给出不确定序下的收益（满意度）矩阵的推导过程;然后,从个体理性视角,结合矩阵博弈的思想构建一种兼顾整体和个体收益的博弈匹配优化模型,并证明模型最优解满足纳什均衡.最后,进一步探讨各种策略选择及其优劣分析.     

A modern Bayesian look at the multi‐armed bandit

A multi‐armed bandit is an experiment with the goal of accumulating rewards from a payoff distribution with unknown parameters that are to be learned sequentially. This article describes a heuristic for managing multi‐armed bandits called randomized probability matching, which randomly allocates observations to arms according the Bayesian posterior probability that each arm is optimal. Advances in Bayesian computation have made randomized probability matching easy to apply to virtually any payoff distribution. This flexibility frees the experimenter to work with payoff distributions that correspond to certain classical experimental designs that have the potential to outperform methods that are ‘optimal’ in simpler contexts. I summarize the relationships between randomized probability matching and several related heuristics that have been used in the reinforcement learning literature. Copyright © 2010 John Wiley & Sons, Ltd.