统计抽样方法在外语单词测验中的应用

本文通过分析一般工业产品计数抽样检验方法与外语单词专项测验的特点,发现二者本质相同。利用统计抽样方法不仅可以获得随机样本(试卷),排除某些主观干扰,同时还可以对受试方和考核方风险率进行评价和选择(按四个分级标准,给出了风险率不同的六组测验方案)。此法已为《大学英语词汇系统软件》采用.     

数值许瓦尔兹－克力斯托夫变换与数值高斯－雅可比型积分

本文研究的主要内容是数值许瓦尔兹─克力斯托夫变换和它所涉及的数值奇异积分问题。利用牛顿─拉夫森迭代法导出了求解许瓦尔兹─克力斯托夫变换各个参数的数值过程。为了提高奇异积分精度,本文对数值高斯─雅可比型积分进行了研究,并用该积分方法对数值许瓦尔兹─克力斯托夫变换公式中出现的奇异积分进行了计算,取得良好结果。本文最后给出了示例,进行了验算。     

m 序列完备递归采样值的存在条件

本文用群论方法讨论了n级m序列完备递归采样值的存在条件,证明了对任意n级m序列,其完备递归采样值存在的充要条件是商群G=Z_p~*/H(其中p=2~n—1,Z_p~*={s|(s,p)=1},H={1,2,2~2,…,2~(n-1))为循环群。在完备递归采样值存在的条件下,求出了完备递归采样值的个数为n.φ(φ(2~n—1)/n)。最后给出了递归采样值的一个重要性质。     

GJB179-86方案自动生成的方法和技术

GJB179-86方案生成系统,涉及GJB179-86中17个表,近25万个基础数据,为尽量节省内存空间,提高程序运行速度,保证软件科学准确、实用方便,笔者在程序设计时,采用了数学公式化处理技术,本文还介绍了“曲线拟合”方法在方案检索程序中的应用,以及有关数表的处理技术。     

舰炮故障诊断中的变速自动采集系统

本文论述一种利用 MZ—80B 微型计算机实现多采样速率的数据自动采集系统,方案设计新颖,软件设计灵活,具有较好的实时性和通用性,对于舰炮武器系统及类似的火炮系统的实时故障诊断具有一定的实用价值.     

宽频带瞬态信号测试方法及应用

本文在分析高速数据采集电路的基础上,采用单片机技术,设计了一种通用性能好、分析频带宽的瞬态信号测试系统。该系统成功地解决了采样速度和频率分辩率的矛盾,提供了一种解决瞬态波形测量的有效方法。     

m 序列的完备递归采样法

本文提出了m 序列递归采样的概念,研究并解决了素数周期m 序列的完备递归采样,对周期为合数的情况得到了一些有用的结论。     

GNSS接收机离散化处理对解扩性能的影响

建立扩频信号防混叠滤波、采样、量化与解扩输出关系的数学解析模型,推导得到解扩输出信噪比的解析表达式。分析与仿真表明,当量化位数大于等于4 bit,解扩得到总的信噪比损失可以分解为由量化引起的损失和滤波加采样引起损失的乘积,且量化器最优限幅系数只与量化位数相关;当量化位数小于4 bit时,信噪比损失在一定条件下可近似为量化损失和滤波加采样损失的乘积。当量化位数大于4 bit、滤波器带宽大于5倍码率、采样频率大于4倍码率时,再增大上述参数引起的信噪比损失波动小于0.05 dB,对解扩性能提升不明显。该结论可为实用型全球导航卫星系统接收机前端离散化处理优化设计提供理论指导。     

Combined variance reduction techniques in fully sequential selection procedures

In the past several decades, many ranking‐and‐selection (R&S) procedures have been developed to select the best simulated system with the largest (or smallest) mean performance measure from a finite number of alternatives. A major issue to address in these R&S problems is to balance the trade‐off between the effectiveness (ie, making a correct selection with a high probability) and the efficiency (ie, using a small total number of observations). In this paper, we take a frequentist's point of view by setting a predetermined probability of correct selection while trying to reduce the total sample size, that is, to improve the efficiency but also maintain the effectiveness. In particular, in order to achieve this goal, we investigate combining various variance reduction techniques into the fully sequential framework, resulting in different R&S procedures with either finite‐time or asymptotic statistical validity. Extensive numerical experiments show great improvement in the efficiency of our proposed procedures as compared with several existing procedures.     

Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty

We propose a novel simulation‐based approach for solving two‐stage stochastic programs with recourse and endogenous (decision dependent) uncertainty. The proposed augmented nested sampling approach recasts the stochastic optimization problem as a simulation problem by treating the decision variables as random. The optimal decision is obtained via the mode of the augmented probability model. We illustrate our methodology on a newsvendor problem with stock‐dependent uncertain demand both in single and multi‐item (news‐stand) cases. We provide performance comparisons with Markov chain Monte Carlo and traditional Monte Carlo simulation‐based optimization schemes. Finally, we conclude with directions for future research.