基于多通道通信技术的高速数据采集器的研制

主要介绍应用多通道通信技术开发研制的高速数据采集器的功能特点 ,对实际研制和使用中的几个关键技术进行了较详细的分析讨论 .应用于流场测试试验的结果表明 ,该系统速度快、稳定性好、功能齐全且自动化程度高 .该系统具有的高精度非常适合于流场测试 ,能确保测试的准确性     

The incentive effect of acceptance sampling plans in a supply chain with endogenous product quality

This article studies a firm that procures a product from a supplier. The quality of each product unit is measured by a continuous variable that follows a normal distribution and is correlated within a batch. The firm conducts an inspection and pays the supplier only if the product batch passes the inspection. The inspection not only serves the purpose of preventing a bad batch from reaching customers but also offers the supplier an incentive to improve product quality. The firm determines the acceptance sampling plan, and the supplier determines the quality effort level in either a simultaneous game or a Stackelberg leadership game, in which both parties share inspection cost and recall loss caused by low product quality. In the simultaneous game, we identify the Nash equilibrium form, provide sufficient conditions that guarantee the existence of a pure strategy Nash equilibrium, and find parameter settings under which the decentralized and centralized supply chains achieve the same outcome. By numerical experiments, we show that the firm's acceptance sampling plan and the supplier's quality effort level are sensitive to both the recall loss sharing ratio and the game format (i.e., the precommitment assumption of the inspection policy). © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

改进预测协方差门限法的采样周期自适应选择算法

传感器采样周期是影响目标跟踪的一个重要参数。现有自适应采样周期策略中,一些算法运算量比较大,计算效率低,不具有一般性。为此提出了一种改进的预测协方差门限法。该算法改进传统采样周期的全遍历寻优策略。最后与几种自适应采样周期算法与固定采样周期算法通过交互式多模型(IMM)滤波算法进行仿真比较。仿真结果表明该算法在目标跟踪过程中能满足跟踪需求,具有较少的计算量,较高的运行效率,比固定采样周期算法更能节约资源。     

基于多分辨分析的数值积分算法

从多分辨分析思想出发 ,推导出一种计算数值积分的算法 ,通过加强迫函数改善其精度。利用张量扩张的原理 ,将其推广到计算多维数值积分。结果表明 ,它不但与传统的Simpson算法有较好的一致性 ,而且对于震荡积分也有较高的精度。     

Clustered coverage orienteering problem of unmanned surface vehicles for water sampling

This study investigates a clustered coverage orienteering problem (CCOP), which is a generalization of the classical orienteering problem. The problem is widely motivated by the emerging unmanned techniques (eg, unmanned surface vehicles and drones) applied to environmental monitoring. Specifically, the unmanned surface vehicles (USVs) are used to monitor reservoir water quality by collecting samples. In the CCOP, the water sampling sites (ie, the nodes) are grouped into clusters, and a minimum number of nodes must be visited in each cluster. With each node representing a certain coverage area of the water, the objective of the CCOP is to monitor as much as possible the total coverage area in one tour of the USV, considering that overlapping areas provide no additional information. An integer programming model is first formulated through a linearization procedure that captures the overlapping feature. A two-stage exact algorithm is proposed to obtain an optimal solution to the problem. The efficiency and effectiveness of the two-stage exact algorithm are demonstrated through experiments on randomly generated instances. The algorithm can effectively solve instances with up to 60 sampling sites.     

基于两阶段抽样法的作战仿真实验方案优选分析

通过作战仿真实验进行实验方案的优选分析研究,分别针对实验方案中的单一实验指标和综合实验指标进行了实验方案优选分析。首先运用两阶段抽样法完成了单一实验指标的实验方案优选分析,进而通过欧几里德贴近度分析了综合实验指标的实验方案优选分析,最后给出了两阶段抽样法在作战仿真实验中进行实验方案优选分析的应用实例。     

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     

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。     

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.