用状态空间法设计低灵敏度 SCFs 的研究

本文从双端接阻无源梯形结构出发,通过两次必要的换标,导出了一种新的完善的 SCFs 的状态空间综合方法。所得到的 SCFs 的状态空间矩阵集的一般形式具有低灵敏度,并且在特定频率下具有零灵敏度。     

智能飞机悬挂物及武器发射/投放管理系统研究

采用人工智能技术研究飞机悬挂物及武器发射／投放管理系统,实现对飞机悬挂物及武器发射／投放的自动化、智能化控制与管理,以此减轻驾驶员的工作负担,提高飞机的作战效能和自身的安全性及生存率,并对系统功能进行了具体的编程仿真。     

离散滑模变结构控制稳定性分析

对流行的离散变结构控制的两种方案——K.Furuta方案和Wang氏方案进行了研究,发现Wang氏方案中的稳定性定理不能成立,其证明不充分。并通过仿真,给出了反例。文章指出控制结构在A区和B区交替变换过程中,系统状态运动的一个循环过程所对应的转移矩阵A_i~*的谱半径小于1,系统才是渐近稳定的。     

舰船利用柴油机冷却水余热作吸收式制冷空调装置热源的研究

对某型舰利用６—１５０Ｃ柴油发电机冷却水余热作为低品位热源进行溴化锂吸收式制冷进行了热力计算和节能分析。计算及分析结果表明：利用６—１５０Ｃ柴油发电机组冷却水余热作为某型舰吸收式空调机组的热源是可行的,它不仅满足该型舰制冷量的要求,还具有明显的节能效果。     

布尔函数不交化的立方体算法

布尔函数的不交化是进行系统可靠度计算中的重要步骤。本文提出了一种进行布尔函数不交化的立方体算法。基于布尔函数的立方体表示法及不交代数,文中定义了立方体的有关运算法则,建立了立方体矩阵不交化算法,并用算例进行了说明。本算法的实现效率高,操作简便。     

Measuring the Impact of Military Spending: How Far Does a DSGE Model Deviate from Reality?

Dunne, Smith, and Willenbockel (2005) argue that the mainstream growth literature has not found military spending to be a significant determinant of economic growth, yet much of the defense economics literature has noted significant effects. This paper revisits this issue by using a DSGE-VAR approach, combining both theoretical and empirical methods. We present that the DSGE approach (estimated with the Bayesian technique) and the Bayesian VAR with the Minnesota Prior both lead to worse in-sample fit than our proposed DSGE-VAR framework. The DSGE-VAR approach reveals that a positive military spending shock boosts the U.S. economy, increasing per capita real GDP growth, consumption, inflation and interest rate. Our results are robust to alternative model specifications. Future investigations such as exploring an optimal military spending policy could adopt the approach in this paper to determine the best model – empirical, theoretical, or a combination of the two.     

Comparison of rank aggregation methods based on inherent ability

Ranking is a common task for selecting and evaluating alternatives. In the past few decades, combining rankings results from various sources into a consensus ranking has become an increasingly active research topic. In this study, we focus on the evaluation of rank aggregation methods. We first develop an experimental data generation method, which can provide ground truth ranking for alternatives based on their “inherent ability.” This experimental data generation method can generate the required individual synthetic rankings with adjustable accuracy and length. We propose characterizing the effectiveness of rank aggregation methods by calculating the Kendall tau distance between the aggregated ranking and the ground truth ranking. We then compare four classical rank aggregation methods and present some useful findings on the relative performances of the four methods. The results reveal that both the accuracy and length of individual rankings have a remarkable effect on the comparison results between rank aggregation methods. Our methods and results may be helpful to both researchers and decision‐makers.     

大型模拟对抗演习回放系统设计

针对大型模拟对抗演习的实际需要,提出了大型模拟对抗演习辅助讲评系统,对其子系统回放系统进行了重点设计。在分析系统功能的基础上,阐述了系统数据流程和可视化表现模式,论述了系统实现的关键技术,最终实现了回放系统。该系统通过对大型模拟对抗演习过程中产生的大量历史数据进行回放或展示,能够在演习结束或者阶段结束后辅助导演部或指挥员对演习过程作出全面客观的评价,从而达到帮助参演人员对演习过程进行分析评估、查找问题、总结经验和教训的目的。     

基于TensorFlow的四旋翼无人机着陆地标识别

针对多旋翼无人机在无人干预情况下的自主着陆问题,提出一种基于迁移学习的地面标识图像检测方法.该方法基于TensorFlow深度学习框架,使用迁移学习技术在地面标识数据集上重新训练Inception-v3模型以构建新的地面标识识别模型.以四旋翼无人机为例,将其拍摄的着陆坪图片与其他地面标识图片作为训练集输入神经网络,通过多次训练校正神经网络参数.实验结果表明,基于迁移学习的四旋翼无人机着陆地标识别比直接基于In-ception-v3模型的识别效果要好得多,在仅有数千张训练图片的情况下,测试准确率超过90％.在Windows下训练、测试的模型可移植到树莓派3B上,完成了基于Python和TensorFlow开发的程序在不同操作系统下运行的验证工作.     

Preparation and characterization of HMX/EVA/hBNNSs micro-composites with improved thermal stability and reduced sensitivity

Hexagonal boron nitride nanosheets(HBNNSs)have huge potential in the field of coating materials owing to their remarkable chemical stability,mechanical strength and thermal conductivity.Thin-layer hBNNSs were obtained by a liquid-phase exfoliation of h-BN powders and incorporated into EVA coatings for improving the safety performance of 1,3,5,7-tetranitro-1,3,5,7-tetrazocane(HMX).HBNNSs and ethylene-vinyl acetate copolymer(EVA)were introduced to HMX by a solvent-slurry process.For com-parison,the HMX/EVA and HMX/EVA/graphene(HMX/EVA/G)composites were also prepared by a similar process.The morphology,crystal form,surface element distribution,thermal decomposition property and impact sensitivity of HMX/EVA/hBNNSs composites were contrastively investigated.Results showed that as prepared HMX/EVA/hBNNSs composites were well coated with hBNNSs and EVA,and exhibited better thermal stability and lower impact sensitivity than that of HMX/EVA and HMX/EVA/G composites,suggesting superior performance of desensitization of hBNNSs in explosives.