基于社会网络可视化分析的数据挖掘

把社会等复杂系统看作网络的思想由来已久.利用社会网络分析的方法,能够对各种社会关系进行精确的量化表征和分析。从而揭示其结构,对一系列当代社会的现象进行更加深入而具体的解释.结合社会网络可视化分析和数据挖掘的理论与方法,引入相关的地理信息,对包含1980-2002年间世界范围内1417例恐怖袭击事件的数据库进行数据分析,以这些恐怖袭击事件各要素节点之间关系作为基本分析单位,对恐怖组织之间的活动模式和发展特点等内在规律进行挖掘与解释,得出有意义的结果.提出的方法可以有效地推广应用于蛋白质结构分析、生物基因分析以及各类社会问题的分析过程.     

海洋检波器性能测试仪信号源的设计

测试仪是用来检测检波器各项性能参数,以便准确地确定检波器的好坏.文中对检波器测试仪的信号源电路进行了具体的分析与设计,采用单片机和AD9850芯片,组成电路简单,但频率、幅度和波形都具有较高精度且利用TDA7261芯片可以进行功率放大的信号源,输出波形参数可以在编程时设定,能满足一些特定场合的需要.     

舰载遥测与红外电视跟踪一体化设计与实现

针对遥测近海面测量时面临的复杂场景干扰以及视觉观感不强等方面的问题,提出在舰载遥测系统上加装红外跟踪系统。采用口径140 mm、焦距260 mm/520 mm的光学系统,能对红外源目标进行跟踪、图像记录和在本地/远程实时监控等功能。提出的Kalman滤波估计算法,能够准确预测目标的速度,使得速度顺馈技术在设备中成功实现。介绍了舰载遥测系统的特点以及一体化设计思想,实现了对遥测系统远、近场电轴的标校以及遥测与红外的互跟踪,并通过实例验证了设计的可行性。     

基于深度强化学习的移动机器人路径规划

为解决传统的深度[Q]网络模型下机器人探索复杂未知环境时收敛速度慢的问题,提出了基于竞争网络结构的改进深度双[Q]网络方法（Improved Dueling Deep Double [Q]-Network,IDDDQN）。移动机器人通过改进的DDQN网络结构对其三个动作的值函数进行估计,并更新网络参数,通过训练网络得到相应的[Q]值。移动机器人采用玻尔兹曼分布与[ε]-greedy相结合的探索策略,选择一个最优动作,到达下一个观察。机器人将通过学习收集到的数据采用改进的重采样优选机制存储到缓存记忆单元中,并利用小批量数据训练网络。实验结果显示,与基本DDQN算法比,IDDDQN训练的机器人能够更快地适应未知环境,网络的收敛速度也得到提高,到达目标点的成功率增加了3倍多,在未知的复杂环境中可以更好地获取最优路径。     

Superpixel Generation by Agglomerative Clustering With Quadratic Error Minimization

Superpixel segmentation is a popular image pre‐processing technique in many computer vision applications. In this paper, we present a novel superpixel generation algorithm by agglomerative clustering with quadratic error minimization. We use a quadratic error metric (QEM) to measure the difference of spatial compactness and colour homogeneity between superpixels. Based on the quadratic function, we propose a bottom‐up greedy clustering algorithm to obtain higher quality superpixel segmentation. There are two steps in our algorithm: merging and swapping. First, we calculate the merging cost of two superpixels and iteratively merge the pair with the minimum cost until the termination condition is satisfied. Then, we optimize the boundary of superpixels by swapping pixels according to their swapping cost to improve the compactness. Due to the quadratic nature of the energy function, each of these atomic operations has only O(1) time complexity. We compare the new method with other state‐of‐the‐art superpixel generation algorithms on two datasets, and our algorithm demonstrates superior performance.     

远心结构光三维系统研究

结构光三维重建技术已广泛应用于工业检测领域,随着工业检测需求的不断提高,工业检测 技术的需求也愈发向微小化和高精度化方向发展。其中,远心镜头具备透视误差小、镜头畸变小、成像失真少等优秀特性,获得越来越多的关注。该文投影仪采用传统镜头,将传统结构光系统中的相机镜头替换为远心镜头,通过对传统两步标定法的改进,对相机的仿射模型进行标定,随后用已标定的相机对投影仪进行参数标定。实验结果显示,所开发的远心结构光系统具备能够实现小视野范围的高精度、高分辨率三维重建,并具有加大的测量景深,可用于半导体器件及微型零部件等目标的高精度 三维检测。     

Distinguishing re-sharing behaviors from re-creating behaviors in information diffusion

Social media plays a fundamental role in the diffusion of information. There are two different ways of information diffusion in social media platforms such as Twitter and Weibo. Users can either re-share messages posted by their friends or re-create messages based on the information acquired from other non-local information sources such as the mass media. By analyzing around 60 million messages from a large micro-blog site, we find that about 69 % of the diffusion volume can be attributed to users’ re-sharing behaviors, and the remaining 31 % are caused by user re-creating behaviors. The information diffusions caused by the two kinds of behaviors have different characteristics and variation trends, but most existing models of information diffusion do not distinguish them. The recent availability of massive online social streams allows us to study the process of information diffusion in much finer detail. In this paper, we introduce a novel model to capture and simulate the process of information diffusion in the micro-blog platforms, which distinguishes users’ re-sharing behaviors from re-creating behaviors by introducing two different components. Thus, our model not only considers the effect of the underlying network structure, but also the influence of other non-local information sources. The empirical results show the superiority of our proposed model in the fitting and prediction tasks of information diffusion.     

Fault diagnosis and fault tolerant control for non-Gaussian time-delayed singular stochastic distribution systems

Stochastic distribution control (SDC) is a new branch of stochastic system control that the system output is the probability density function (PDF) of the output. In practice, some algebraic relations exist between the input and the weights of SDC systems, leading to a singular state space model between the weights and the control input which increases the complexity of the system. The ignorance of time delay in practical systems will make the effectiveness of the fault diagnosis (FD) and fault tolerant control (FTC) be reduced. In this paper, the linear B-spline basis functions are used to approximate the output PDF. A FD approach based on the adaptive observer is established to diagnose the size of fault in the singular time-delayed SDC system. With the fault diagnosis information, a fault tolerant controller based on PI tracking control scheme is constructed to make the post-fault PDF still track the given distribution. The post-fault closed-loop stability analysis with the practical fault tolerant controller is carried out based on the Lyapunov stability theorem. Finally, a numerical simulation is provided to demonstrate the effectiveness of the proposed approach.     

Adaptive actuator failure compensation for multivariable feedback linearizable systems

A feedback linearization‐based adaptive control scheme is developed for multivariable nonlinear systems with redundant actuators subject to uncertain failures. Such an adaptive controller contains a direct adaptive actuator failure compensator to compensate the uncertain actuator failure, a nonlinear feedback to linearize the nonlinear dynamics, and a linear feedback to stabilize the linearized system. The key new design feature is the estimation of both the failure patterns and the failure values, for direct adaptive actuator failure compensation, newly developed for multivariable feedback linearizable nonlinear systems. With direct control signal adaptation, the adaptive failure compensation design ensures closed‐loop stability and asymptotic output tracking in the presence of actuator failure uncertainties. Simulation results from an application to attitude control of a near‐space vehicle dynamic model are presented to verify the desired system performance with adaptive actuator failure compensation. Copyright © 2015 John Wiley & Sons, Ltd.     

一种多幂次滑模趋近律设计与分析

针对传统滑模趋近律使系统存在抖振现象、收敛速度较慢及动态响应不平滑等问题, 提出一种多幂次滑模趋近律.该趋近律通过三个幂次项系数在系统趋近过程不同阶段进行针对性地调节, 使系统动态响应过程的收敛速度大幅度提高, 且无抖振现象.理论验证了其存在性、可达性及稳定性, 并详细推导了趋近速率及干扰稳定界.以航天器姿态机动控制系统为例, 对比仿真结果表明该趋近律下, 系统的动态过程有较大改善并消除了抖振, 且在存在模型不确定性及外加干扰作用下, 系统仍可较快地收敛到平衡点附近的邻域内.