基于ARM的太阳跟踪控制系统设计

为了改进对太阳的跟踪精度,提高太阳能的利用率,设计了一种基于ARM的新型的太阳跟踪控制系统;该系统利用32位ARM嵌入式微处理器芯片LPC2290作为控制器,通过程序对跟踪机构水平、俯仰两个方向的控制,实现对太阳的全跟踪;并在此基础上利用安装在跟踪机构上的角度传感器,对跟踪机构进行定时的误差校正,改进跟踪的精度;通过试验阶段的运行分析,此设计跟踪精度能够满足碟式太阳能热发电的需要,系统性能稳定,成本较低,功能扩展性强,具有较高的实用价值.     

基于ADS的脉冲压缩雷达系统仿真与性能分析

在高级设计系统ADS仿真平台上,开发了一套具有良好通用性和灵活性的脉冲压缩雷达系统模型库,为今后开发大规模雷达系统模型库和进行复杂雷达系统仿真打下了基础;在此工作基础上,以巴克码脉冲压缩信号为例,建立了相应的雷达系统模型,并结合系统性能分析的需求,在该系统仿真设计过程中引入蒙特.卡罗模型,较全面地得到了系统基本性能指标值;由这些指标值可以看出,该巴克码脉冲压缩雷达系统性能良好;仿真结果与理论值和真实系统值相符,从而正确地完成了系统的方案论证和性能评估。     

A DR algorithm based on artificial potential field method

Considering player entity’s motion regularity into DR (Dead Reckoning) algorithm can improve its prediction accuracy in MMOG (Massively Multiplayer Online Games), a novel DR algorithm was proposed to solve this problem in this paper. First the artificial potential field model of player entities is created, and then the acceleration of player entities is weighted with the acceleration produced by the potential field force and the acceleration reckoned by the traditional DR algorithm. In order to calculate the weight, Q-Learning algorithm is used. The experiments show that the method can improve prediction accuracy and reduce the network traffic.     

Detecting Overlapping Community Structures in Networks

Community structure has been recognized as an important statistical feature of networked systems over the past decade. A lot of work has been done to discover isolated communities from a network, and the focus was on developing of algorithms with high quality and good performance. However, there is less work done on the discovery of overlapping community structure, even though it could better capture the nature of network in some real-world applications. For example, people are always provided with varying characteristics and interests, and are able to join very different communities in their social network. In this context, we present a novel overlapping community structures detecting algorithm which first finds the seed sets by the spectral partition and then extends them with a special random walks technique. At every expansion step, the modularity function Q is chosen to measure the expansion structures. The function has become one of the popular standards in community detecting and is defined in Newman and Girvan (Phys. Rev. 69:026113, 2004). We also give a theoretic analysis to the whole expansion process and prove that our algorithm gets the best community structures greedily. Extensive experiments are conducted in real-world networks with various sizes. The results show that overlapping is important to find the complete community structures and our method outperforms the C-means in quality.     

高速可配置Rijndael算法的设计与实现

针对网络通信的安全要求,给出了在集成电路设计中实现Rijndael算法的高吞吐率解决方案。对算法实现进行了优化,具有支持密钥长度和数据长度的可变选择与组合配置,加密和解密工作通道完全独立,全双工安全高速通信等特点。已通过了FPGA的验证与电路实现。通过对比分析综合仿真结果,该实现相对于目前已知的实现方案在性能和速度上具有很大的优势。     

基于GML／KML的空间数据库研究

空间数据库是当前GIS技术的一个热点,GML已经成为空间数据编码、传输、存储、发布的国际标准,而KML也已经成为一个OGC标准。以GML／KML为基础构架空间数据库,解决了传统GIS空间数据库存在的诸多问题。通过比较空间数据库管理模式,分析采用GML／KML技术建立空间数据库的优点,着重探讨GML／KML技术构建空间数据库的框架。最后通过“数字九寨沟”实例进行验证,得出结论GML和KML是进行空间数据库设计的理想技术。     

EM算法研究与应用

引入了可处理缺失数据的EM算法.EM算法是一种迭代算法,每一次迭代都能保证似然函数值增加,并且收敛到一个局部极大值.对EM算法的基本原理和实施步骤进行了分析.算法的命名,是因为算法的每一迭代包括两步:第一步求期望(Expectation Step),称为E步;第二步求极大值(Maximization Step),称为M步.EM算法主要用来计算基于不完全数据的极大似然估计.在此基础上,把EM算法融合到状态空间模型的参数估计问题.给出了基于Kalman平滑和算法的线性状态空问模型参数估计方法.     

基于二维属性的高维数据聚类算法研究

聚类就是按照一定的要求和规律对事物进行区分和分类的过程.在这一过程中没有任何关于类别的先验知识,也没有教师的指导,仅靠事物间的相似性作为类属划分的准则,因此属于元监督分类的范畴.聚类分析则是指用数学的方法研究和处理给定对象的分类.针对目前很多聚类算法只能对低维数据进行聚类的问题,提出了一种改进的相异度度量方法对二维属性的高维数据采用层次分裂算法进行聚类,而且根据用户指定的参数聚类,并对传统相异度度量和改进的相异度度量方法的聚类结果进行比较,发现改进的相异度度量方法更适用于二维属性的高维数据的聚类.     

Linear control of a boiler-turbine unit: analysis and design

Linear control of a boiler–turbine unit is discussed in this paper. Based on the nonlinear model of the unit, this paper analyzes the nonlinearity of the unit, and selects the appropriate operating points so that the linear controller can achieve wide-range performance. Simulation and experimental results at the No. 4 Unit at the Dalate Power Plant show that the linear controller can achieve the desired performance under a specific range of load variations.     

MCR-ALS与HPLC-DAD相结合同时测定喜树碱及其衍生物

将多元曲线分辨-交替最小二乘(MCR-ALS)与高效液相色谱-二极管阵列检测器(HPLC-DAD)检测相结合,对伊立替康、7-乙基-10-羟基喜树碱和喜树碱的色谱重叠峰进行分辨。采用MCR-ALS同时分析多个数据矩阵组成的方式,以克服MCR-ALS在单一重叠峰数据矩阵的解析中遇到的缺秩问题。讨论了影响分辨结果的几种因素,包括被分析物之间的光谱相似度、色谱峰的分离度和干扰物浓度等。分辨所得光谱还原率高,定量结果可靠,说明MCR-ALS能有效地解决喜树碱及其衍生物色谱分析中重叠峰的二阶校正问题。