线膛火炮身管剩余寿命的神经网络模型研究

利用前馈式人工神经网络方法,根据试验数据,建立了某火炮身管剩余寿命(RL)模型;并用该模型研究了各特征截面内径改变量对弹丸初速改变量的影响,以及弹丸初速改变量与总内径改变量间的关系。     

舰用计算机局部网络通信协议的设计

介绍了舰用计算机局部网络通信协议的设计,重点描述了设计中为提高实时性和可靠性所采用的一些具体技术措施,其中包括:简化ISO/OSI—RM 参考模型,并与IEEE8024标准协议兼容,采用VLSI 技术设计网络接口卡。同时,对其中一些关键技术,如逻辑环的建立与维护、信息的优先级发送与实时响应、数据缓冲区的结构与管理都作了说明。     

防空系统中空中目标威胁评估方法研究

针对当前对空中目标威胁评估研究的不足,提出了一种防空系统中评估目标威胁度的新方法,其思想在于将空中目标的威胁因子分为定量指标和定性指标,其中定量指标包括目标速度、目标高度等可以直接获取的指标,该部分指标通过隶属函数直接得到威胁值;定性指标包括目标类型、目标意图等不能直接获取的指标,通过贝叶斯网络进行推理以得到静态威胁值。最后通过AHP 方法对各个指标威胁值进行加权得到总威胁值。该方法的特点在于定性分析与定量分析的结合,通过仿真算例验证了该方法的有效性与可行性。     

The structural origins of social cohesion: the dynamics of micro-solidarity in 1991–1995 Wars of Yugoslav Succession

This article explores the dynamics of social cohesion on the frontline. It attempts to show how micro-level solidarities largely depend on macro level organisational processes. I argue that frontline social cohesion is often the product of social development linked with the organisational structure. This general argument is applied to the case studies of two armed forces involved in the 1991–1995 Wars of Yugoslav Succession – the Croatian Army (HV) and the Bosnian Serb Army (VRS). Drawing on in-depth interviews with the former combatants I show how HV social cohesion played an important role in winning the war and how these networks of micro-level solidarity were shaped by long term organisational development.     

An infrared target intrusion detection method based on feature fusion and enhancement

Infrared target intrusion detection has significant applications in the fields of military defence and intelligent warning. In view of the characteristics of intrusion targets as well as inspection difficulties, an infrared target intrusion detection algorithm based on feature fusion and enhancement was proposed. This algorithm combines static target mode analysis and dynamic multi-frame correlation detection to extract infrared target features at different levels. Among them, LBP texture analysis can be used to effectively identify the posterior feature patterns which have been contained in the target library, while motion frame difference method can detect the moving regions of the image, improve the integrity of target regions such as camouflage, sheltering and deformation. In order to integrate the advantages of the two methods, the enhanced convolutional neural network was designed and the feature images obtained by the two methods were fused and enhanced. The enhancement module of the network strengthened and screened the targets, and realized the background suppression of infrared images. Based on the experiments, the effect of the proposed method and the comparison method on the background suppression and detection performance was evaluated, and the results showed that the SCRG and BSF values of the method in this paper had a better performance in multiple data sets, and it’s detection performance was far better than the comparison algorithm. The experiment results indicated that, compared with traditional infrared target detection methods, the proposed method could detect the infrared invasion target more accurately, and suppress the background noise more effectively.     

基于L-M算法改进BP网络的信息对抗能力评估

在未来密集和复杂的电磁环境中,快速、客观地评估敌我双方的信息对抗能力具有重要的意义。目前通常采用的人工打分方法具有一定的主观性,且周期较长,难于满足战场瞬息万变的需求。提出了一种基于L evenberg-M arquardt算法改进的BP神经网络信息对抗能力评估方法,以某组信息对抗数据为训练数据,对改进BP神经网络进行训练,并进行了验证性的仿真试验。仿真结果表明:改进BP神经网络能客观有效地评估信息对抗能力,较大程度地提高了神经网络的收敛速度、缩短了评估时间。     

串口RS-485网络设计及应用

介绍RS-485串口相关电气接口标准技术知识,提出一个典型的RS-485网络模型以及分析在某产品中的应用和列举网络常见故障.     

神经网络在联合火力打击目标价值分析中的应用

针对联合火力打击中目标价值的特点,运用BP神经网络理论对目标价值进行分析,并建立了联合火力打击目标价值分析指标体系,设计了BP神经网络模型;通过定义学习代价函数、确定函数输出信号、修正函数信号、网络初始化等改进BP算法对目标价值进行了分析,得到了目标打击序列分类.算例验证了该算法的合理、高效、稳定,在联合火力打击中目标优选分类方面具有广泛的实用意义.     

战场赛博空间电子战应用研究

首先阐述和分析了赛博空间和电子战的概念和特点,给出了电子战在赛博空间中的定位。然后探讨了电子战在赛博空间中的应用,给出了电子战在赛博空间中可能应用的几大方面。最后总结了赛博空间电子战面临的关键技术与挑战。