太阳米粒结构相关哈特曼-夏克波前传感模拟研究

基于互相关因子和绝对差分算法以及相关哈特曼－夏克波前传感器的基本原理，根据室内模拟太阳米料结构研究了低对比度扩展目标情况下应用相关哈特曼－夏克波前传感器探测波前误差的可行性，结果表明，相关哈特曼－夏克波前传感器能够有效探测光学波前误差。     

非线性ABS型算法的一个统一收敛定理

本文讨论非线性方程组的算法的局部收敛性，给出了一个统一的收敛定理．该定理相当一般，不仅包含ＡＢＳ型方程，而且对目前常用的许多方法也都适用．     

解与HJB方程相关的拟变分不等式的松弛法

本文对关于HJB方程的拟变分不等式提出了松弛算法，也给出了基于上述算法的区域分解方法，并建立了相应的收敛性定理。     

Combinatorial approximation algorithms: a comparative review

This paper is a comparative review of three related books:Giorgio Ausiello, Pierluigi Crescenzi, Giorgio Gambosi, Viggo Kann, Alberto Marchetti-Spaccamela, Marco Protasi, Complexity and Approximation (Combinatorial Optimization Problems and Their Approximability Properties), second printing, Springer, Berlin, 2003, ISBN 3-540-65431-3, 524 pp., €53.45 (first printing 1999).Juraj Hromkovi?, Algorithmics for Hard Problems (Introduction to Combinatorial Optimization, Randomization, Approximation, and Heuristics), second edition, Springer, Berlin, 2003, ISBN 3-540-44134-4, 544 pp., €53.45 (first printing 2001).Vijay Vazirani, Approximation Algorithms, second printing, Springer, Berlin, 2002, ISBN 3-540-65367-8, 380 pp., €37.40 (first printing 2001).     

模糊聚类分析的新算法

提出了一种模糊聚类分析的新算法——追踪法 ,解决了以往模糊聚类分析计算量过大以及难于编程实现的问题 .该方法尤其适用于大规模数据的模糊聚类分析 ,对于模糊聚类分析的推广使用有重要意义 .     

s~(1/2)=630GeV pp碰撞中微喷注的新分析

根据喷注判定的圆锥法来判断喷注，重新分析了ＵＡ１－１９８５年的６３０ＧｅＶ非单衍ｐｐ碰撞实验数据。分析发现对事件样本，单事件平均横动量ｐ与多重数ｎ是正关联的，而对喷注事件子样本则是负关联的；分析了微喷注产生嵉墓亓屯斯亓砻魑⑴缱⒉丛从诜侨砉毯透呓仔вΓ徊⑹状未邮笛樯瞎鄄獾轿⑴缱⒓浯嬖诖罂於燃涓裟谖蘖Ｗ拥氖吕治隽宋⑴缱⒉贝嬖诖罂於龋纾幔鸬募Ｏ蟆     

视觉模式识别网络及光电实现

在形态学网络及改进的Ｈａｍｍｉｎｇ网络基础上，提出视觉模式识别网络及训练算法，形态学网络作为特征提取网络，具有相对图像平移和尺度不变的特性，改进的Ｈａｍｍｉｎｇ网络加速完成特征矢量的分类操作。经过学习的视觉模式识别网络，可完成图像特征的提取，实现相对于图像平移和尺度不变的模式识别，在此基础上，建立了光电视觉模式识别体系，从而实现实时模式识别。     

Experiments on the practical I/O efficiency of geometric algorithms: Distribution sweep versus plane sweep

We present an extensive experimental study comparing the performance of four algorithms for the following orthogonal segment intersection problem: given a set of horizontal and vertical line segments in the plane, report all intersecting horizontal-vertical pairs. The problem has important applications in VLSI layout and graphics, which are large-scale in nature. The algorithms under evaluation are our implementations of distribution sweep and three variations of plane sweep. Distribution sweep is specifically designed for the situations in which the problem is too large to be solved in internal memory, and theoretically has optimal I/O cost. Plane sweep is a well-known and powerful technique in computational geometry, and is optimal for this particular problem in terms of internal computation. The three variations of plane sweep differ by the sorting methods (external versus internal sorting) used in the preprocessing phase and the dynamic data structures (B-tree versus 2-3-4-tree) used in the sweeping phase. We generate the test data by three programs that use a random number generator while producing some interesting properties that are predicted by our theoretical analysis. The sizes of the test data range from 250 thousand segments to 2.5 million segments. The experiments provide detailed quantitative evaluation of the performance of the four algorithms, and the observed behavior of the algorithms is consistent with their theoretical properties. This is, to the best of our knowledge, the first experimental algorithmic study comparing the practical performance between external-memory algorithms and conventional algorithms with large-scale test data.