窄带干扰下GPS接收机捕获性能的研究

针对GPS接收机抗干扰能力强的特点,分析了窄带干扰对接收机的捕获性能的影响.在扩频理论的基础上,给出了GPS C/A码接收机信号捕获的数学模型,计算得出平均捕获时间与捕获时间方差,给出窄带干扰下的接收机信号捕获的仿真结果.结果表明,当窄带干扰功率超过一定的值时,会导致GPS接收机捕获性能的严重恶化.     

多址通信的跳频码序列的研究

在跳频多址通信中,为了减少用户之间的互相干扰,保证良好的同步以及其它工作性能,要求跳频码序列具有较好的互相关特性和自相关特性。本文首先分析了具有较好互相关特性和自相关特性的码序列的理论上受到的限制,然后着重分析了它们的构造和产生。     

电抗元件网络的优化设计方法

以信息与编码技术为主要理论依据,应用微计算机技术,提出了电抗元件网络的优化设计方法:采用二进制编码对网络进行控制,以网络分辩率δ与2~((?))的乘积δ·2~((?))作为权电阻的阻值。对该种网络的有关特性作了分析。     

快速边缘跟踪与边界链码的获取

本文首先讨论了边缘跟踪的常用方法,并指出了其存在的缺点,而后提出了虚象点与虚链的概念,并讨论了它们的性质。在此基础上,提出了快速边缘跟踪的算法和边界链码的获取。     

电子在材料中输运的蒙特卡罗模拟

介绍了电子输运问题的蒙特卡罗方法的基本原理和步骤。电子输运过程的模拟采用了“浓缩历史”蒙特卡罗方法 ,电子随机游动步长根据能量步划分 ,在每个电子游动步内 ,电子的能量损失为非辐射 (碰撞 )能量损失和辐射 (韧致辐射 )能量损失之和 ,其中非辐射能量损失通过对Landau公式的随机抽样得到 ,辐射能量损失以及韧致辐射光子的产生通过利用Bethe Heitler的随机抽样处理 ,在每个电子游动步结束时电子的出射角的抽样利用Gouddsmit Saunderson多重散射公式 ,电子 -电子的散射利用Moller截面公式进行抽样。最后对电子在航天用合金铝平板材料中的输运进行了模拟计算并给出了计算结果     

A chessboard model of the U‐boat war in the Atlantic with applications to signals intelligence

This paper uses a simple Monte Carlo model to analyze the influence of signals intelligence on the Second World War's Battle of the Atlantic. The principle measure of effectiveness is the number of U‐boat days of attack to which convoys were subjected. A secondary measure is the number of convoyed ships sunk. The model is validated against historical data and then used to explore the effectiveness of the two sides' signals intelligence. Allied use of signals intelligence is shown to have been capable of completely offsetting German use of signals intelligence, and then some. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

码资源受限系统中的碎片整理算法及定时机制的研究

在分析传统码资源静态分配算法缺陷的基础上,研究了直接合并碎片整理算法和最小分支搜索不完全码碎片整理算法.同时研究了碎片整理算法中的关键问题:碎片整理的时机,即定时机制问题.提出了一种获取定时参数的方法,并利用计算机仿真工具对定时机制进行了仿真,验证了理论结论.     

高超声速圆柱绕流中驻点热流的稀薄效应

采用Fay-Riddell关系式、直接模拟Monte Carlo方法和基于直接模拟Monte Carlo流场温度的Fourier传热三种热流表达方式,分别对比研究了不同来流克努森数(Kn)和不同来流马赫数(Ma)的结果,以期从微观视角给出经典连续方法在稀薄流区高估驻点热流的新理解。结果表明,驻点热流的稀薄效应体现在三个方面:一是温度跳跃,削弱温度梯度导致驻点热流降低;二是壁面附近平动非平衡,导致Fourier热传导定律失效且高估热流;三是壁面约束,致使Fourier热传导定律在距壁面3倍分子平均自由程内高估热流。     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.