Performance evaluation of a production/inventory system with periodic review and endogenous lead times

This paper considers a discrete time, single item production/inventory system with random period demands. Inventory levels are reviewed periodically and managed using a base‐stock policy. Replenishment orders are placed with the production system which is capacitated in the sense that there is a single server that sequentially processes the items one at a time with stochastic unit processing times. In this setting the variability in demand determines the arrival pattern of production orders at the queue, influencing supply lead times. In addition, the inventory behavior is impacted by the correlation between demand and lead times: a large demand size corresponds to a long lead time, depleting the inventory longer. The contribution of this paper is threefold. First, we present an exact procedure based on matrix‐analytic techniques for computing the replenishment lead time distribution given an arbitrary discrete demand distribution. Second, we numerically characterize the distribution of inventory levels, and various other performance measures such as fill rate, base‐stock levels and optimal safety stocks, taking the correlation between demand and lead times into account. Third, we develop an algorithm to fit the first two moments of the demand and service time distribution to a discrete phase‐type distribution with a minimal number of phases. This provides a practical tool to analyze the effect of demand variability, as measured by its coefficient of variation, on system performance. We also show that our model is more appropriate than some existing models of capacitated systems in discrete time. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

一种调频调相混合调制信号及抗干扰性能分析

针对线性调频信号形式简单,易被敌方截获和干扰的特点,提出了一类脉内线性调频和子脉冲相位调制相结合的具有多种变化形式的混合调制脉冲压缩信号。MATLAB仿真分析表明,与单纯线性调频信号相比,该混合调制信号产生和处理简单,既保持了线性调频信号的优点,又提高了抗截获和抗干扰能力。     

相干信号源DOA估计改进ESPRIT算法研究

在目标方位估计(DOA)的众多算法中,ESPRIT是一种运算速度快、精度高的常用算法,但它不能解相干信号。提出一种基于观测数据直接空间平滑的改进型ESPRIT算法,解决了常规ESPRIT算法不能解相干、对信噪比要求高等问题。该方法适用于所有信号(非相干和相干信号)的目标方位估计。     

基于改进PLOW算法的干涉相位滤波

针对合成孔径雷达干涉相位滤波问题,提出了一种改进的分块局部最佳维纳滤波算法（Patch-based Locally Optimal Wiener, PLOW）。该算法是加性高斯白噪声下的线性最小均方误差估计（Linear Minimum Mean Square Estimation, LMMSE）,利用目前图像滤波最前沿的技术——非局部技术,来联合估计图像的一、二阶矩。针对干涉相位中噪声的空变性,在应用中提出了两点改进：首先,估计噪声的标准差时,用均值代替中值;其次,根据噪声标准差的最大值和均值的比值,自适应的确定类的数量。经过仿真和实测数据验证,改进后的PLOW算法是有效的,并优于其他三种算法。     

GPS接收机模糊搜索粗时定位方法

由于难以获得免时定位算法所需的接收机概略位置,提出模糊搜索的粗时定位方法。为减小搜索空间,在位同步后优选几何精度因子值较好的4颗卫星通过遍历伪距模糊的方式进行位置估计,并基于伪距残余均方根最小准则选出最合理的位置估算结果。根据概略位置恢复所有卫星的完整伪距。利用5状态的免时定位算法估计接收机位置。使用11个国际卫星导航服务观测站的观测数据对算法进行验证,结果表明,在概略位置未知情况下该方法能够实现粗时定位,且定位精度与直接使用完整伪距的精时最小二乘定位精度相当。     

基于DSP和FPGA的载波移相脉冲生成方法

在研究了三电平全桥变流器工作原理和载波移相原理的基础上,设计生成了基于数字信号处理器(DSP)和现场可编程门阵列(FPGA)的载波移相PWM脉冲,用于驱动变流器工作。重点介绍了由DSP和FPGA生成载波移相PWM脉冲的基本原理、系统构成及实现方法,其核心思想是FPGA通过数据地址总线接收DSP输出的移相角与FPGA内部生成的三角波进行二逻辑比较,从而产生移相角可变的PWM脉冲,以满足变流器全工况范围实时控制的需要。通过优化设计,使DSP和FPGA各自的优势得以有效利用。仿真分析表明:该方法计算速度快、控制精度高,同时具有扩展性好、可靠性高等优点。实验结果与仿真结果吻合,验证了该方法的上述优点。     

科氏流量计信号相位差测量新算法

对科氏流量计信号进行处理时,传统相位差测量算法存在较大误差。为更好地抑制频谱泄露,提高相位差测量精度,在传统DTFT算法的基础上,通过矩形窗和汉宁窗卷积运算构造出一种新窗——RHC窗。计及负频率成分的影响,提出了一种基于RHC窗的DTFT相位差测量新算法。详细阐述了新算法的原理,并与传统DTFT算法进行了对比仿真,验证了新算法的有效性。     

气液同轴离心式喷嘴雾化特性实验研究

采用自行设计的两相喷雾实验设备和测量装置,通过ＭＦ激光散射测粒仪,对液氧液氢火箭发动机所用量气液同轴离心式喷嘴后方喷雾液滴的平均直径ＭＭＤ和液滴尺寸分布指数ｎ等雾化特性,进行了试验研究,测量了Ａ型喷嘴在不同气体和液体喷注压降、不同空间位置的喷雾特性。分析了气体喷注压降一定时液体喷注压降对雾化特性的影响规律,以及当液体喷注压降一定时气体喷注压降对雾化特性的影响规律,得出了一些有意义的结论。研完结果对气液同轴离心式喷嘴设计有一定的指导意义。     

信号分割修正聚类的星座图恢复算法

通过分析载波估计频偏、信号长度对星座图恢复的影响,采用将长信号分割为短信号的方法减小频偏对星座图恢复的干扰,并通过旋转叠加修正的方法解决了由信号长度减小导致码元失去历遍性而带来的星座图恢复不完整问题,最后根据信噪比大小选取不同聚类算法进行聚类并再次修正,实现了星座图对称的幅相调制信号的星座图完整恢复。多次仿真表明,该算法对频偏估计精度的要求可以降低1~2个数量级,减小了参数估计的工作量,使因参数估计精度不高而带来的信号后续分析困难问题得到了良好解决。     

A note on the forecast performance of temporal aggregation

Earlier research on the effects of nonoverlapping temporal aggregation on demand forecasting showed the benefits associated with such an approach under a stationary AR(1) or MA(1) processes for decision making conducted at the disaggregate level. The first objective of this note is to extend those important results by considering a more general underlying demand process. The second objective is to assess the conditions under which aggregation may be a preferable approach for improving decision making at the aggregate level as well. We confirm the validity of previous results under more general conditions, and we show the increased benefit resulting from forecasting by temporal aggregation at lower frequency time units. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 489–500, 2014