基于神经网络的地形匹配方法研究

提出了基于神经网络实现多特征融合的地形匹配算法，充分利用地形的各种不同的统计特征和几何特征，构造了一种地形匹配网络模型．通过对实时图和基准图的分析，给出了计算网络节点之间的权值函数，建立了网络系统能量方程，通过求系统的最小能量得到最佳匹配位置．由于网络能融合地形的不同统计特征和几何特征，所以算法大大提高了系统的抗干扰能力和定位精度，适合于实时图容易发生畸变的地形匹配领域．实验结果表明，定位精度和抗干扰能力均优于传统的地形匹配方法．     

网络拓扑自动布局技术的研究与实现

文中在网络拓扑发现以及图形显示子系统设计中,以面向对象语言的方式组织了相关的拓扑信息数据结构,同时提出了一套基于中心层次式布局的图形显示方法,解决了布局过程中的手工调整问题。并且给出了一个拓扑发现显示实例。     

金隆闪速炉精矿喷嘴的优化

介绍金隆公司闪速炉精矿喷嘴的结构特点和运行情况,针对运行中存在的问题,通过优化操作参数、改进结构,喷嘴的性能得到了很大改善。     

Internet连接共享的设计与实现

介绍了Internet连接共享、网络拓扑结构,说明了安装网络硬件,指出了安装服务器网络软件和配置客户机的网络属性.     

Obtaining complete 2 D view representation of polyhedra using concept of seedling single-view area

This article deals with construction of complete 2 D exact view models of polyhedral objects for visual identification systems. In particular, a new method and an algorithm views generation using the view sphere with perspective concept are described. A set of views generated by this method forms a complete view representation of the object. The method of ensuring completeness of the view representation by controlling covering of the view space (by single-view areas) is used in the presented algorithm. The perspective projection used for calculating the views, the total, tight covering of the view sphere by the single-view areas and -dimensionality of the views ensure, in our opinion, unambiguous and proper identification of polyhedral objects. The method consists in calculating single (any) view, determining the corresponding single-view area (so-called seedling single-view area) and then spiral propagation of neighbouring single-view areas until the whole view sphere is covered by them (i.e., until the border register containing the border between the covered and uncovered parts of the view sphere becomes empty). Having a complete set of single-view areas, we get a complete set of views as well. A method of determining single-view areas for convex polyhedra is also presented.     

Natural resonance-based feature extraction with reduced aspect sensitivity for electromagnetic target classification

This paper presents a model-based electromagnetic feature extraction technique that makes use of time-frequency analysis to extract natural resonance-related target features from scattered signals. In this technique, the discrete auto-Wigner distribution of a given signal is processed to obtain a partitioned energy density vector with a significantly reduced sensitivity to aspect angle. Each partition of this vector contains, in the approximate sense, spectral distribution of the signal energy confined to a particular subinterval of time. Selection of sufficiently late-time partitions provides target features with a markedly increased target discrimination capacity. The potential of the suggested technique and the practical issues in its implementation are demonstrated by applying it to realistic target classification problems with very encouraging results.     

Iris detection using intensity and edge information

In this paper we propose a new algorithm to detect the irises of both eyes from a face image. The algorithm first detects the face region in the image and then extracts intensity valleys from the face region. Next, the algorithm extracts iris candidates from the valleys using the feature template of Lin and Wu (IEEE Trans. Image Process. 8 (6) (1999) 834) and the separability filter of Fukui and Yamaguchi (Trans. IEICE Japan J80-D-II (8) (1997) 2170). Finally, using the costs for pairs of iris candidates proposed in this paper, the algorithm selects a pair of iris candidates corresponding to the irises. The costs are computed by using Hough transform, separability filter and template matching. As the results of the experiments, the iris detection rate of the proposed algorithm was 95.3% for 150 face images of 15 persons without spectacles in the database of University of Bern and 96.8% for 63 images of 21 persons without spectacles in the AR database.     

关于最佳鉴别特征维数问题的讨论

该文对最佳鉴别特征的最佳维数问题进行了详细的讨论．文章首先对最佳维数问题进行了界定，然后指出了两种最佳特征维数为c-1维的情况即以某些基于矩的可分性判据(准则函数)为优化目标的最优特征和以某些特殊的分类器错误率为优化目标的最优特征．最后该文运用方差分析法对最佳鉴别特征进行特征选择使之代入最小距离分类器后识别率最大．     

用遗传BP网络进行图像边缘检测

该文提出了一种基于遗传算法与图像特征向量的边缘检测方法。由于噪声的干扰,常规的图像边缘检测方法往往效果不佳,因此在充分考虑边缘和噪声本质区别的基础上,构造具有较强抗噪能力的特征向量;然后用样本图像对多层前馈神经网络采用遗传学习算法和误差反向传播算法(BP)相结合进行训练,即先用遗传学习算法进行全局训练,再用BP算法进行精确训练,使网络收敛速度加快和避免局部极小。最后,将训练后的网络用于图像的边缘检测。实验证明这种方法是有效的。     

层次式交换网络——未来Internet的一种新框架

1 背景新的应用需求和通讯技术的进步是驱动网络体系结构和网络协议发展的主要力量。自1995年开始,Internet数据流量以每年超过100％的速度增长,估计2002年,数据业务量将超过话音业务量,并在未来三年里将占总业务量的90％。同时,数据应用也从传统应用(电子邮件、文件传输、WWW等)向实时多媒体应用(IP电话、视频会议、VOD、交互游戏、虚拟现实、远程医疗和远程教育等)迅速发展,要求