实验教学遥测系统中的一种码型反变换方法

在遥测系统中有许多种数字信号码型可以使用。在遥测解调分系统中 ,通常采用 NRZL 码作为输出码型 ,这就需要将系统输入的其它码型反变换为 NRZL 码。文中介绍一种在实验教学遥测系统中采用的利用匹配滤波、门限判决、采样、移位、异或的手段来实现码型反变换的方法。     

一种适于动态环境的盲多用户检测算法

比较两种盲多用户检测算法在动态环境中的收敛性能,并通过计算机进行模拟仿真。其中一种是能随输入信号矢量变化而变化的变步长最小输出能量盲算法;另一种是既保持最小输出能量检测器的全局收敛性,又具有最小均方误差检测器高输出信干比优点的判决反馈变步长盲算法。利用前者在动态强干扰下收敛快及后者在稳态时输出信干比高的优势,将二者结合起来应用到动态环境中,提高系统性能,同时抑制多址干扰和窄带干扰。     

自激励门限自回归模型研究与应用

本文利用自激励门限回归分析方法，建立新生儿体重的门限自回归模型SETAR（2；2；1：5），得到令人满意的结果。     

抗辐射模拟CMOS集成电路研究与设计

为研究宇宙辐射环境中航天器里的模拟互补金属氧化物半导体(Complementary Metal Oxide Semiconductor,CMOS)集成电路性能和各种效应,并在辐射效应所产生机制的基础上,从设计和工艺方面提出了模拟CMOS集成电路主要抗辐射加固设计方法.在宇宙环境中,卫星中的模拟CMOS集成电路存在CMOS半导体元器件阈值电压偏离、线性跨导减小、衬底的漏电流增加和转角1/f噪声幅值增加.所以提出了3种对模拟CMOS集成电路进行抗辐射加固的方法:1)抗辐射模拟CMOS集成电路的设计;2)抗辐射集成电路版图设计;3)单晶半导体硅膜(Silicon on Insulator,SOI)抗辐射工艺与加固设计.根据上面的设计方法研制了抗辐射加固模拟CMOS集成电路,可以取得较好的抗辐射效果.     

理论门槛值的研究

阐述了应力强度因子门槛值△Ｋｔｈ的重要性，讨论了理论门槛值的概念，分析了工程门槛值的局限性，提出了理论槛值的求解方法，实例分析显示了理论门槛值研究，无论对于工程应用或理论研究均具有重要意义。     

Comparison of decision tree methods for finding active objects

The automated classification of objects from large catalogs or survey projects is an important task in many astronomical surveys. Faced with various classification algorithms, astronomers should select the method according to their requirements. Here we describe several kinds of decision trees for finding active objects by multi-wavelength data, such as REPTree, Random Tree, Decision Stump, Random Forest, J48, NBTree, AdTree. All decision tree approaches investigated are in the WEKA package. The classification performance of the methods is presented. In the process of classification by decision tree methods, the classification rules are easily obtained, moreover these rules are clear and easy to understand for astronomers. As a result, astronomers are inclined to prefer and apply them, thus know which attributes are important to discriminate celestial objects. The experimental results show that when various decision trees are applied in discriminating active objects (quasars, BL Lac objects and active galaxies) from non-active objects (stars and galaxies), ADTree is the best only in terms of accuracy, Decision Stump is the best only considering speed, J48 is the optimal choice considering both accuracy and speed.     

基于决策支持系统的高校人事管理信息化建设

人事管理信息化程度影响着高校人事工作效率和人事决策的实施,以决策支持系统的视角来研究高校人事管理信息化,对进一步加快人事管理的现代化进程、促进人事管理信息系统的建设,最终实现高等学校人事管理的全面信息化具有重要的理论和现实意义.     

基于星间测距的卫星自主导航中异常值剔除方法

在星间观测值数据传输中,由于种种因素有个别值与其他值截然不同,对定轨精度造成了严重的影响,必须对这些违反测量过程规律的异常测量值进行剔除。提出一种运用轨道积分器与设定随时间实时变化的门限值对星间距离观测值进行异常值剔除的方法。仿真结果表明,这种异常值剔除方法能够成功剔除观测误差大于等于180m的异常值,较精确、实时地剔除了对定轨结果影响较大的异常值,在卫星导航领域具有一定的应用价值。     

Comparison of alternative route selection strategies based on simulation optimization

Air traffic flow management (ATFM) is a collaborative process between the airspace provider and the airspace users. The result of the collaboration should be an outcome that maxi-mizes the utility of the system without excessively penalizing any of the agents. This paper develops a discrete-event simulation model which consists of aggregate departure/arrival airports, flight routes, and sectors for evaluating the alternative collaborative route selection strategy. Given the different perspectives from air traffic control center (ACC) and airlines, eight performance-metrics and five alternative route selection strategies represent the past, current and proposed air traffic flow management operations that were evaluated. The Monte Carlo method combined with the Optimal Computing Budget Allocation (OCBA) simulation optimization technique is employed to assess the performance of different strategies. A case study of the upper air routes in central and southern China shows that the proposed model can be readily implemented to simulate different kinds of air traffic flow management strategies and predict the effect of changes on the airspace sys-tem. It also shows that the proposed alternative collaborative route selection strategy is an effective way in alleviating the en-route traffic congestion.     

Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal’s cultivation, steppes and bar soil.