Double window acceptance sampling

We introduce the concept of a sequential double window procedure and compare the resulting acceptance test with both a fixed sample size method as well as with the Wald sequential probability ratio test. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

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.     

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。     

宽带数字接收机高速信号处理技术

具有1 GHz瞬时带宽的宽带数字接收机是当前数字接收机研究的热点,也是雷达对抗侦察数字接收机的发展方向。详细讨论了宽带数字接收机的几种高速信号处理技术,包括单比特瞬时测频技术、多相滤波信道化技术、基于FFT的信道化接收机和射频带通采样微波数字接收机,最后提出了在宽带中频数字接收机高速信号处理领域需要深入研究的有关技术。     

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。     

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.     

空气采样感烟火灾探测系统在大空间中的应用

介绍了高灵敏度空气采样感烟火灾探测系统的性能、结构特点及工作原理,并重点讨论了此系统在高大空间的应用。     

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。     

信号的直接采样理论

经典的采样定理建立了带限信号与其均匀采样值之间的联系。本文对采样定律作了三点补充 :1)给出在定理条件不满足时 ,由均匀采样值恢复的信号与原信号的误差表达式 ;2 )用简洁的方法分析了带通信号的均匀采样问题 ,得到了采样率应满足的条件 ;3)研究了一种特殊的非均匀采样情况 ,给出了采样率的可取范围以及由非均匀采样重构原信号的公式。这些都是对经典采样定理的丰富和深化。