基于复杂网络的维修保障力量体系建模方法

针对传统的层级式维修保障力量体系在维修保障过程中暴露出的缺陷,从维修保障力量体系与复杂网络的相似性角度出发,提出用复杂网络理论来研究维修保障力量体系。在对维修保障力量活动过程进行网络化抽象的基础上,建立了维修保障力量网络的拓扑模型,提出了描述维修保障力量网络的特征量。以师维修保障力量体系作为研究对象建立了网络拓扑模型,并对该网络结构作了适当改进。通过一系列对比发现改进后的网络更有利于维修保障,这为维修保障力量体系建设提供了一种新思路和新方法。     

放大转发双向中继网络的移动级联信道统计特征分析

针对放大转发协议下双向中继网络移动级联信道,为了分析其统计特征,结合用户完成信息交互的过程,将移动级联信道分解为传输部分和干扰部分两个时间过程。依据它们的双高斯乘积特点,分别给出了对应的一阶概率密度分布、二阶自相关函数和多普勒功率谱的表达式。与此同时,通过采用Gamma分布对级联信道进行了概率近似,得到了描述移动级联信道时变特性的电平通过率和平均衰落时间等指标的近似计算式。借助数值仿真验证了上述表达式的正确性。     

Financial versus human resources in the Greek‐Turkish arms race: A forecasting investigation using artificial neural networks

This paper aims at forecasting the burden on the Greek economy resulting from the arms race against Turkey and at concentrating on the leading determinants of this burden. The military debt and the defence share of GDP are employed alternatively in order to approximate the measurement of the arms race pressure on Greece, and the method used is that of artificial neural networks. The use of a wide variety of explanatory variables in combination with the promising results derived, suggest that the impact on the Greek economy resulting from this arms race is determined, to a large, extent, by demographic factors which strongly favour the Turkish side. Prediction on both miltary debt and defence expenditure exhibited highly satisfactory accuracy, while the estimation of input significance, indicates that variables describing the Turkish side are often dominant over the corresponding Greek ones.     

基于复杂网络理论的作战系统结构拓扑模型研究

基于复杂网络理论,分析了信息化作战系统网络结构,构建了传统作战系统和信息化作战系统拓扑模型的生成算法,并通过对传统作战系统和信息化作战系统结构拓扑模型度量性质的比较,说明了信息化战争下的作战系统结构特点,为进一步研究网络化战争提供了良好的模型基础．     

The Trust Paradox in Nuclear Smuggling

ABSTRACT

This article explores the paradox of trust in the largest nuclear smuggling operation involving highly enriched uranium (HEU) discussed in open source literature. In the first effort to understand the type, extent, and role of trust in nuclear smuggling enterprises, it draws from literature on trust development in legitimate businesses as well as criminal enterprises. Observed behavioral patterns in this case challenge traditional notions of the internal dynamics of temporary groups engaged in nuclear smuggling and operational realities of such activities. The article seeks to explain why individuals agree (and continue) to operate in this high-risk environment, unbound by close personal ties, without any effort to verify the background, motives, or qualifications of the fellow conspirators. It offers ways to advance current nonproliferation efforts in non-state actor interdiction by exploiting the environment of shallow trust in temporary groups.     

具有时滞的Cohen—Grossberg神经网络的Hopf分支全局存在性研究

摘要：利用泛函微分方程的度理论,研究一类具有时滞的Cohen-Grossberg神经网络的全局分支的存在性,研究结果为该类神经网络的应用设计提供理论基础．     

Strategic intelligence during coin detention operations – relational data and understanding latent terror networks

One aspect of the global “War on Terror” that has received limited coverage in the academic literature is the problem of detained persons as it relates to intelligence. This is a surprising oversight, given the number of detainees that the USA has been responsible for (over 25,000 were in custody in Iraq alone at one time during its peak). The detention environment offers a prime strategic intelligence opportunity for the US intelligence community to study the tactics and organizations of individuals who have been removed from the overall conflict. In this article an easily implemented collection program is recommended to be deployed in US/coalition detention centers. The primary recommendation is to gather relational data on detainee communication, both authorized and illicit, and to use these data to perform network analyses of terrorist groups and their individual members.     

LEACH—DRT算法中基于神经网络的数据预测算法

为了保证无线传感器网络中数据的完整性,针对基于LEACH路由协议的动态轮时间算法存在的问题,提出一种基于人工神经网络的数据预测算法。该动态轮时间算法中,部分簇因调整后的轮时间不足以完成数据的采集而丢失数据。数据预测算法结合传感器节点数据具有时空相关性的特点,将时空延迟算子引入神经网络模型,并通过建立的神经网络模型对数据进行预测。仿真时采用伯克利英特尔实验室的传感器数据,通过Mafl软件对模型进行测试并分析仿真结果。实验结果表明：该算法对连续多个数据的预测效果理想,预测误差始终保持在较低水平。     

基于Sub-Nyquist采样的单通道频谱感知技术

宽带频谱感知技术在认知无线电中具有广泛的应用。基于时分的思想,将信号采集时间以固定长度的时间片进行划分,分别与不同的伪随机码信号相乘,经过低通滤波和sub-Nyquist采样,利用采样数据求出信号的频率支集。与已有的多通道频谱感知结构相比,本文用相对简单的单通道结构实现,同样能够利用低速率的采样点完成频谱感知。仿真实验结果表明,在信号的频率支集未知的情况下,该算法能够有效利用sub-Nyquist采样的数据实现频谱感知。     

基于最大比合并的循环平稳频谱协作检测

多天线空间分集和多用户协作检测是提高认知无线电频谱检测性能的2种关键技术,由此提出了基于循环平稳特征的多天线多用户频谱协作检测方法.首先接收器在频域按照最大比合并的方法合并各天线接收信号,对合并信号进行初步频谱判决.然后在多用户中按照K/N融合准则进一步做频谱协作检测.仿真分析表明,综合利用信号循环平稳特征和协作检测技术可有效改善认知无线电系统检测性能.