Efficient multinomial selection in simulation

Consider a simulation experiment consisting of v independent vector replications across k systems, where in any given replication one system is selected as the best performer (i.e., it wins). Each system has an unknown constant probability of winning in any replication and the numbers of wins for the individual systems follow a multinomial distribution. The classical multinomial selection procedure of Bechhofer, Elmaghraby, and Morse (Procedure BEM) prescribes a minimum number of replications, denoted as v*, so that the probability of correctly selecting the true best system (PCS) meets or exceeds a prespecified probability. Assuming that larger is better, Procedure BEM selects as best the system having the largest value of the performance measure in more replications than any other system. We use these same v* replications across k systems to form (v*)^k pseudoreplications that contain one observation from each system, and develop Procedure AVC (All Vector Comparisons) to achieve a higher PCS than with Procedure BEM. For specific small-sample cases and via a large-sample approximation we show that the PCS with Procedure AVC exceeds the PCS with Procedure BEM. We also show that with Procedure AVC we achieve a given PCS with a smaller v than the v* required with Procedure BEM. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 459–482, 1998     

On gamma estimation via matrix kriging

In financial engineering, sensitivities of derivative prices (also known as the Greeks) are important quantities in risk management, and stochastic gradient estimation methods are used to estimate them given the market parameters. In practice, the surface (function) of the Greeks with respect to the underlying parameters is much more desired, because it can be used in real‐time risk management. In this paper, we consider derivatives with multiple underlying assets, and propose three stochastic kriging‐based methods, the element‐by‐element, the importance mapping, and the Cholesky decomposition, to fit the surface of the gamma matrix that can fulfill the time constraint and the precision requirement in real‐time risk management. Numerical experiments are provided to illustrate the effectiveness of the proposed methods.     

水平集方法中速度停止项函数的改进

对速度停止项函数的研究发现,现今的速度停止项采用的单一全局阈值法很难使经典水平集算法得到较准确的分割效果。为此,提出了一种新的速度停止项函数,该函数通过引入变阈值较好的区分了图像的边缘区与同质区,以使采用该速度停止项函数的水平集方程实现在同质区加速演化,在边缘区停止演化的目的。实验结果表明,采用速度停止项函数能够使水平集方法获取更好的分割结果。     

多退化模式下的电子装备可靠性建模

通常加速退化分析中退化失效只考虑或者假设只有一个退化通道,而实际上很多情况下会存在多退化模式.产品的各个退化通道间的关系存在随机性,即任意两个退化通道间不可能只是单一的相关或者独立.在考虑这种相关性的条件下,深入研究了电子产品的性能退化理论和机理,提出了两个多退化模式竞争失效的数学模型,分别阐述了退化通道相关与独立的两种不同情况下产品可靠度评估方法.     

MSPWVD-HOUGH变换的多目标分辨和雷达回波参数估计

传统的时频分析方法,如Winger Ville Distribution,smoothed pseudo Wigner-Ville distribution等在多目标分辨的时候,无法同时在时频分辨率和抑制交叉项两方面同时达到较好的效果,所提出的MSPWVD解决了这一问题,MSPWVDHOUGH还可在低信噪比的情况下检测出多目标,并估算其参数,可利用来进行雷达成像的运动补偿.     

Inference for the maximum cell probability under multinomial sampling

This article investigates inference for p_max, the largest cell probability in multinomial trials for the case of a small to moderate number of trials. Emphasis focuses on point and interval estimation. Both frequentist and Bayesian approaches are developed. The results of extensive simulation investigation are included as well as the analysis of a set of crime data for the city of New Orleans taken from the National Crime Survey.     

基于SDG的物资供应动态过程定性模型的建立

针对物资供应过程仿真中仿真信息不明确、不完整、比较模糊而又难于定量化描述的问题,引入定性仿真中符号定向图(SDG)法,定性分析了通用物资供应的过程.首先,提取物资供应过程中各定性环节要素,对其建立定性关系方程和定性模型(SDG模型图),然后,根据方程和模型仿真结果给出具体环节因素的取值标准.通过实例验证得出了用定性建模的方法研究物资供应动态过程更加简明实际的结论.     

飞机电传操纵系统控制律的神经网络实现

现代多功能战机多用电传操纵系统替代传统的机械杆系,但由于飞机的多变量、强耦合和不稳定等强非线性特点,使得其电传控制律的工程实现相当复杂.为此,对电传操纵系统控制律的神经网络实现方法进行了研究.通过利用径向基函数(RBF)网络良好的非线性跟踪性能,探讨了用RBF网络实现电传控制律的一般方法,并以某型飞机电传操纵系统纵向通道为例,对该方法进行了验证.