A nonparametric Bayes approach to decide system burn-in time

Burn-in is the preconditioning of assemblies and the accelerated power-on tests performed on equipment subject to temperature, vibration, voltage, radiation, load, corrosion, and humidity. Burn-in techniques are widely applied to integrated circuits (IC) to enhance the component and system reliability. However, reliability prediction by burn-in at the component level, such as the one using the military (e.g., MIL-STD-280A, 756B, 217E [23–25]) and the industrial standards (e.g., the JEDEC standards), is usually not consistent with the field observations. Here, we propose system burn-in, which can remove many of the residual defects left from component and subsystem burn-in (Chien and Kuo [6]). A nonparametric model is considered because 1) the system configuration is usually very complicated, 2) the components in the system have different failure mechanisms, and 3) there is no good model for modeling incompatibility among components and subsystems (Chien and Kuo [5]; Kuo [16]). Since the cost of testing a system is high and, thus, only small samples are available, a Bayesian nonparametric approach is proposed to determine the system burn-in time. A case study using the proposed approach on MCM ASIC's shows that our model can be applied in the cases where 1) the tests and the samples are expensive, and 2) the records of previous generation of the products can provide information on the failure rate of the system under investigation. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 655–671, 1997     

Algorithms for computing waiting time distributions under different queue disciplines for the D-BMAP/PH/1

A queueing system characterized by the discrete batch Markovian arrival process (D-BMAP) and a probability of phase type distribution for the service time is one that arises frequently in the area of telecommunications. Under this arrival process and service time distribution we derive the waiting time distribution for three queue disciplines: first in first out (FIFO), last in first out (LIFO), and service in random order (SIRO). We also outline efficient algorithmic procedures for computing the waiting time distributions under each discipline. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 559–576, 1997     

时频分析方法及其在自导信号检测中的应用

首先引入时频分析的概念,介绍了短时傅里叶变换、Wigner—Ville分布和连续小波变换的数学表示和性质.其次基于经典检测理论,讨论并比较了它们在高斯白噪声背景下对确知信号的检测问题.最后对它们在自导信号检测应用中的有关问题进行了分析,并指出了需进一步研究的方向.     

基于多层循环并行化的负载平衡优化

负载平衡是并行处理中的一个重要概念。参与一个程序执行的各处理机所承担的工作量是否均衡直接影响该程序的并行性能。本文对面向MPP系统程序循环级并行化中负载平衡的优化进行了探讨,提出了优化策略及其实施算法。     

火炮身管寿命的分布函数

本文运用可靠性理论和《130mm 加农炮剩余寿命的一种预测模型》一文的结果,证明火炮身管寿命服从 Weibull 分布,并以130mm 加农炮为实例,给出参数的比值估计方法.     

概率分布在库存弹药贮存可靠性研究中的应用

本文探讨在库存弹药贮存可靠性研究中应用概率分布的特点,阐述了几种常用概率分布的可靠性特性和物理模型,分析了弹药系统的可靠性结构特征和贮存失效特性,最后提出了在库存弹药的贮存可靠性研究中选择概率分布的依据。     

泊松分布的错误图样对纠错码译码性能的影响

为了在"比特级"层面对纠错码进行更深入的研究,提出了一种服从泊松分布的错误图样分布模型。通过一定的方法产生符合泊松分布特性的二进制序列,并使"1"的数目在整个序列中可控,以此来产生所需的错误图样。同时,以卷积码、RS码以及RS+卷积级联码为研究对象,以随机错误为参照,分别分析了该错误图样下三者的译码性能。仿真结果表明,基于泊松分布的错误图样对卷积码和级联码的影响要大于随机错误图样,而随机错误图样对RS码的影响更大。     

中程空空导弹冲淡式干扰模型

中程空空导弹的末制导主动雷达一方面提高了中程空空导弹作战效能和载机的生成概率,另一方面也为对中程空空导弹实施冲淡式干扰提供了机会。基于冲淡式干扰的基本原理建立了中程空空导弹的冲淡式电子干扰模型,分析了各种不同攻防对策下的冲淡式干扰的效果及其变化趋势,在此基础上讨论了对抗双方在冲淡式电子对抗中的最优对策。     

装甲装备修理对象修理工作量的分布模型及应用

通过论述当今典型军队战时修理机构任务的划分,给出了装甲装备修理对象按照修理工作量和按照修理时间分布的2种模型,结合俄陆军各级修理机构修理时限的划分,计算得到了典型装甲装备的技术故障和战损产生的修理对象在各级修理机构的概率分布,为开展战损研究提供了一条新途径,对提高技术保障方案的准确性有积极作用。     

相依风险下的超额赔款再保险

本文通过求二次效用函数的货币期望效用的最大值来确定自留额，认为索赔次数服从二元泊松分布，超额赔款再保险的保费按期望值原理进行计算。