基于局部子图匹配的SLAM 方法

针对现有的SLAM 解决方法在机器人被“绑架”时失效的问题,提出了基于局部子图匹配的方法．该 方法对现有的SLAM 解决构架进行了改进,提出交点最优匹配的特征相关算法,并且将奇异值分解方法引入机器人 定位．最后,在结构化环境下将本方法和基于扩展卡尔曼滤波器的方法进行比较,讨论了基于局部子图匹配的方法 在结构化环境中解决机器人“绑架”问题的有效性和可行性．     

基于MPI的FDTD并行算法及其优化策略

由高性能PC机通过网络互联构成的集群(COW)并行计算系统上应用基于消息传递(Message Passing)的方式实现FDTD的并行算法,获得了足够的加速比,有效地解决了传统的FDTD方法计算电大尺寸目标电磁散射问题时的不足.通过区域分割,各个子区域在边界处与其相邻的子区域进行场值的数据传递,从而实现了FDTD算法的并行化.利用并行FDTD方法研究了电磁波的介质层的散射,结果表明并行算法和串行计算结果的一致性,并有效提高计算效率.最后还给出了对算法进行通信隐藏的优化方法,进一步提高了并行计算的效率.     

基于LSA和pLSA的多文档自动文摘

本文提出一种基于LSA和pLSA的多文档自动文摘策略。首先,将多个文档切分成自然段,以自然段作为聚类单位。采用了新的特征提取方法构建词-自然段矩阵,利用LSA对词-自然段矩阵进行奇异值分解,使得向量空间模型中的高维表示变成在潜在语义空间中的低维表示。然后,采用pLSA将数据转换成概率统计模型来计算。在文摘生成的过程中采用基于质心的文摘句挑选办法得到文摘并输出。实验表明,本文提出的方法有效地提高了生成文摘的质量。     

多主体诊断系统的建模及应用

将智能主体技术引入复杂故障诊断领域,建立了一种基于多主体的复杂诊断系统结构模型,对诊断问题任务辨识、分解、各主体的内部诊断机制、多主体间的交互、协作、关联模型以及诊断决策问题等进行了深入研究,并重点描述了诊断问题的故障分解与控制策略。在某企业安全监控系统的应用中,该模型能快速、准确地进行故障成因分析,给出合理的决策意见,取得了很好的诊断结果,显著提高了企业的安全运行效率。     

Effects of the Si/Al atomic ratio on the activity of Cu-ZSM-5 catalysts for nitric oxide decomposition

A review of literature data for nitric oxide decomposition over Cu-ZSM-5 catalysts leads us to conclude that the turnover frequency depends on the Si/Al atomic ratio in a way opposite to the trend suggested by Iwamoto and co-workers and considered correct by Shelef in a recent letter published in this Journal. In particular we show that the turnover frequency increases with the number of Al atoms per unit cell (i.e. decreasing the Si/Al atomic ratio). This result suggests that the most active sites for NO decomposition over Cu-ZSM-5 catalysts may contain two close copper ions.     

Antimagic labeling and canonical decomposition of graphs

An antimagic labeling of a connected graph with m edges is an injective assignment of labels from {1,…,m} to the edges such that the sums of incident labels are distinct at distinct vertices. Hartsfield and Ringel conjectured that every connected graph other than K₂ has an antimagic labeling. We prove this for the classes of split graphs and graphs decomposable under the canonical decomposition introduced by Tyshkevich. As a consequence, we provide a sufficient condition on graph degree sequences to guarantee an antimagic labeling.     

Parallelization of a dynamic SVD clustering algorithm and its application in information retrieval

We describe an implementation of a parallel document clustering scheme based on latent semantic indexing, which uses singular value decomposition. Given a set of documents, the clustering algorithm is dynamic in the sense that it automatically infers the number of clusters to be output. The parallel version has been implemented on a LAN and on a dual‐core system. Experimental evaluation of the algorithm shows an average speed‐up of 6.22 for the LAN implementation and an average speed‐up of 3.71 for the dual‐core implementation, while still maintaining a precision and recall in the range [0.85, 1]. To put these implementations in the context of information retrieval, we use the parallel clustering algorithm and develop a document similarity search system. The similarity search system shows good performance in terms of precision and recall. Copyright © 2010 John Wiley & Sons, Ltd.     

3带紧支撑的正交小波

本文首先通过Householder矩阵扩充构造了3带紧支撑的正交小波．当尺度函数具有紧支撑对称正交性时,本文通过仿酉矩阵对称扩充构造了3带紧支撑对称的正交小波,并且研究了所构造对称小波的结构．所构造小波函数的支撑不超过尺度函数的支撑,构造方法容易推广到一般d带的情形．另外,本文还给出了容易实施的显式构造算法．最后,给出了构造算例．     

Structure damage diagnosis using neural network and feature fusion

A structure damage diagnosis method combining the wavelet packet decomposition, multi-sensor feature fusion theory and neural network pattern classification was presented. Firstly, vibration signals gathered from sensors were decomposed using orthogonal wavelet. Secondly, the relative energy of decomposed frequency band was calculated. Thirdly, the input feature vectors of neural network classifier were built by fusing wavelet packet relative energy distribution of these sensors. Finally, with the trained classifier, damage diagnosis and assessment was realized. The result indicates that, a much more precise and reliable diagnosis information is obtained and the diagnosis accuracy is improved as well.