Generalized KKM Type Theorems in FC-Spaces with Applications (I)

The class KKM(X,Y) (resp., s-KKM(X,Y,Z)) of set-valued mappings with KKM (resp., s-KKM) property is introduced in FC-spaces without any convexity structure. Some generalized KKM (resp., s-KKM) type theorems are proved in FC-spaces under much weak assumptions. As applications, some new section theorems and coincidence theorems are established in FC-spaces. These theorems generalize many known results in literature. The further applications of these results will be given in a follow-up paper.     

一维光子晶体缺陷模激光器的放大特性

光子晶体中引入缺陷后将形成缺陷模,这些缺陷模在增益介质中将被放大形成激光。基于麦克斯韦方程和速率方程相结合的模型,用时域有限差分法(FDTD)计算和分析了一维单缺陷光子晶体激光器中缺陷模的空间分布和频谱特性,以及这些缺陷模的放大特性,主要研究了缺陷层的厚度、晶体层数对缺陷模放大特性的影响。模拟结果显示,类似于传统激光腔的腔模,这些缺陷模能够被放大,形成激光。调整缺陷层的厚度、晶体层数等结构参量,将改变缺陷模的谐振,激射频率以及空间分布,这将直接影响激射阈值和饱和特性。增加晶体的层数,激光器的阈值将降低,饱和值将增加,但晶体层数增加到一定限度时,这种增减趋势变弱。模拟结果证明了有效层数的存在。     

Skew Models II

If g and G are the pdf and the cdf of a distribution symmetric around 0 then the pdf 2g(u)G(λ u) is said to define a skew distribution. In this paper, we provide a mathematical treatment of the skew distributions when g and G are taken to come from one of Pearson type II, Pearson type VII or the generalized t distribution.      

岛状皮瓣修复足前部皮肤缺损修复的进展

归纳足前部的生物力学和应用解剖研究结果,足前部的皮肤缺损将会导致足的功能障碍,重点讨论了各种岛状皮瓣修复足前部皮肤缺损的优缺点,并对足内侧皮瓣修复足前部皮肤缺损提出了问题和展望.     

“A priori” estimates, uniqueness and existence of positive solutions of Yamabe type equations on complete manifolds

We study the asymptotic behaviour of non-negative solutions of Yamabe type equations on a complete Riemannian manifold. Then we provide a comparison result, based on a form of the weak maximum principle at infinity, which together with the “a priori” estimates previously obtained, yields uniqueness under very general Ricci assumptions. The paper ends with an existence result and an application to the non-compact Yamabe problem.     

BP神经网络在光学相关器相关峰识别中的应用

光学相关识别是图像识别的重要方法，有效识别相关器输出平面的相关峰信号是保证光学相关器图像识别准确性的关键。由于激光器输出功率的波动、光学系统本身的误差以及SLM器件本身带来的噪声，采用一般的阈值方法很难达到理想的效果。该文提出对相关器的输出平面进行预处理，充分考虑相关信号的形状信息，提取感兴趣区域(ROI)，采用BP神经网络对输入矢量进行计算，可达到对相关峰信号和噪声的有效分类识别，从而提高了光学相关器识别的可靠性，降低了误判的概率。     

A simple solution of the van der Waerden permanent problem

The van der Waerden permanent problem was solved using mainly algebraic methods. A much simpler analytic proof is given using a new concept in optimization theory which may be of importance in the general theory of mathematical programming.     

一类脉冲中立型时滞抛物方程组的振动性

研究一类脉冲中立型时滞抛物方程组解的振动性,得到了该类方程组在两类不同边界条件下所有解振动的若干充分条件.     

中高分辨力遥感图像中飞机目标自动识别算法研究

提出了一种中高分辨力的航空航天遥感图像中飞机目标快速自动识别的新算法。在分割和分类过程中充分利用飞机目标的先验知识,提出了一种改进区域分割方法,并应用树分类器对飞机目标进行自动识别。所提出的改进区域分割方法较好地实现了区域分割中阈值的准确自动选取,克服了复杂背景图像中小目标的全局阈值自动分割的失效问题。采用二叉树分类器,通过提取简单的目标几何特征,分层进行种类识别,提高了识别速度,降低了漏检率和虚警率。运用该方法进行了实验。结果表明,识别率达到了100%。     

On bulk-service MAP/PH L,N /1/N G-Queues with repeated attempts

We consider a retrial queue with a finite buffer of size N, with arrivals of ordinary units and of negative units (which cancel one ordinary unit), both assumed to be Markovian arrival processes. The service requirements are of phase type. In addition, a PH^L,N bulk service discipline is assumed. This means that the units are served in groups of size at least L, where 1≤ L≤ N. If at the completion of a service fewer than L units are present at the buffer, the server switches off and waits until the buffer length reaches the threshold L. Then it switches on and initiates service for such a group of units. On the contrary, if at the completion of a service L or more units are present at the buffer, all units enter service as a group. Units arriving when the buffer is full are not lost, but they join a group of unsatisfied units called “orbit”. Our interest is in the continuous-time Markov chain describing the state of the queue at arbitrary times, which constitutes a level dependent quasi-birth-and-death process. We start by analyzing a simplified version of our queueing model, which is amenable to numerical calculation and is based on spatially homogeneous quasi-birth-and-death processes. This leads to modified matrix-geometric formulas that reveal the basic qualitative properties of our algorithmic approach for computing performance measures. AMS Subject Classification: Primary 60K25 Secondary 68M20 90B22.