一种高效的全局K-均值算法

针对全局K-均值算法时间复杂度大的问题,提出一种增量选择初始聚类中心的新方法。选择数据集中周围分布最密集的样本作为第一个初始聚类中心,选择最小化目标函数贡献大,并且和已有聚类中心距离远的样本作为下一个初始聚类中心。改进算法减少了增量选取初始聚类中心时的计算量,降低了时间复杂度。实验证明,改进算法与全局K-均值算法、快速全局K-均值算法相比,在不影响聚类效果的基础上,减少了聚类时间,与优化初始聚类中心的算法相比,聚类效果更优。     

Hybrid Kalman and unscented Kalman filters for INS/GPS integrated system considering constant lever arm effect

In inertial navigation system(INS) and global positioning system(GPS) integrated system, GPS antennas are usually not located at the same location as the inertial measurement unit(IMU) of the INS, so the lever arm effect exists, which makes the observation equation highly nonlinear. The INS/GPS integration with constant lever arm effect is studied. The position relation of IMU and GPS’s antenna is represented in the earth centered earth fixed frame, while the velocity relation of these two systems is represented in local horizontal frame. Due to the small integration time interval of INS, i.e. 0.1 s in this work, the nonlinearity in the INS error equation is trivial, so the linear INS error model is constructed and addressed by Kalman filter’s prediction step. On the other hand, the high nonlinearity in the observation equation due to lever arm effect is addressed by unscented Kalman filter’s update step to attain higher accuracy and better applicability. Simulation is designed and the performance of the hybrid filter is validated.     

一种虹膜色素块检测与分类方法

针对现有虹膜识别系统中全局纹理特征提取方法忽略了纹理类型信息的问题,提出了一种针对全局性纹理中虹膜色素块的检测与分类方法.该方法利用灰度聚类法实现虹膜图像中色素块可能存在区域的初定位,依据坑洞和色素斑这两类色素块的灰度空间分布特性,定义一组区域特征参数作为分类特征向量,利用支持向量机实现二者的检测与分类.算法对图库中图像的坑洞和色素斑的检测正确率分别为99.2%和86.5%,对无特征纹理存在的虹膜图像检测正确率为87.2%.实验结果表明,该方法具有较高的正确率,能够满足虹膜识别系统的纹理特征提取要求.     

A composite particle swarm algorithm for global optimization of multimodal functions

During the last decade, many variants of the original particle swarm optimization （PSO） algorithm have been proposed for global numerical optimization, hut they usually face many challenges such as low solution quality and slow convergence speed on multimodal function optimization. A composite particle swarm optimization （CPSO） for solving these difficulties is presented, in which a novel learning strategy plus an assisted search mechanism framework is used. Instead of simple learning strategy of the original PSO, the proposed CPSO combines one particle＇s historical best information and the global best information into one learning exemplar to guide the particle movement. The proposed learning strategy can reserve the original search information and lead to faster convergence speed. The proposed assisted search mechanism is designed to look for the global optimum. Search direction of particles can be greatly changed by this mechanism so that the algorithm has a large chance to escape from local optima. In order to make the assisted search mechanism more efficient and the algorithm more reliable, the executive probability of the assisted search mechanism is adjusted by the feedback of the improvement degree of optimal value after each iteration. According to the result of numerical experiments on multimodal benchmark functions such as Schwefel, Rastrigin, Ackley and Griewank both with and without coordinate rotation, the proposed CPSO offers faster convergence speed, higher quality solution and stronger robustness than other variants of PSO.     

分布式云数据库复合Trigger新机制

为灵活高效地解决在不同的场景下,更新云数据库系统中缓存的全局共享数据表的问题,本文提出了一种在云服务端分布式数据库使用的复合触发器新型的软件架构,并基于数据库触发器技术,引入了直接、间接和复合Trigger的3种机制,这3种Trigger机制的引用,使来自业务支撑模块的数据变化,或是实时业务模块的数据变化,其前端的应用程序都可以及时高效的更新缓存。该研究提高了系统的灵活性,稳定性和鲁棒性。特别复合Trigger机制,可以避免大量的跨网络数据交互发生,提高了应用的服务质量。     

基于膜计算的C波段异常信号特征选择

提出一种基于膜计算的C波段异常信号特征选择算法。该算法将膜结构分为2层：基本膜和表层膜。首先在基本膜中结合模糊C均值（ FCM）聚类、粗糙集和遗传算法（ GA）实现局部寻优,然后将局部最优解传送给表层膜,最后在表层膜区域中再一次使用遗传算法实现全局优化。通过对无线电监测C波段异常信号特征库进行仿真实验,发现该算法在C波段异常信号的特征选择上比使用遗传算法、约翰逊算法所得的条件属性更简单且优化效果更好。     

国际化视野下城市公共艺术案例研究

公共艺术是一个城市的名片,代表城市的形象,放大了城市的功能价值,因此,城市公共艺术建设越来越被关注和重视.国际上,人们对公共艺术功能的解读逐渐清晰,不再将其简单看作城市装饰品,而是更高地定位在创造和提升城市美学品质,注重物质文化消费,平衡生态环境,促进自然社会可持续发展等方面.通过对相关城市公共艺术案例的解读分析,试图揭示公共艺术的价值取向,营造理想的公共艺术文化生态.     

具有非局部源和边界流抛物型方程组解的性质

研究了一类具有非局部源及边界流抛物型组解的性质,通过构造方程组的上、下解及运用比较定理,得到了方程组解整体存在及解在有限时刻爆破的充分条件。由此得到,当反应项和扩散项的指数满足不同条件时,方程组的解具有不同的性质。     

基于遗传算法的模板匹配算法研究与设计

针对一般模板匹配算法计算量大并且容易陷入局部最优等缺点,研究了使用遗传算法对模板匹配进行全局寻优的算法。在被检测图形和模板已知的情况下,建立了模板匹配的归一化的数学模型。通过对模型计算量的分析,设计了能够减少模型求解计算量的算法。进一步使用遗传算法对设计的算法进行了改进,该算法能使模板匹配快速收敛到全局最优解。算例表明,本算法能有效解决模板匹配的全局寻优问题,并且使模板匹配效率有了明显提高。这一研究为图形处理者提供了科学的模板匹配方法。     

一类二次比式和最优解的研究

对于二次比式和问题的最优解问题,提出了一种罚函数法以及单纯形分枝定界算法.利用指数函数及线性化技术,将约束优化问题转化为易于求解的无约束优化问题,最终给出了算法.