FAST FEATURE RANKING AND ITS APPLICATION TO FACE RECOGNITION

A fast feature ranking algorithm for classification in the presence of high dimensionahty and small sample size is proposed. The basic idea is that the important features force the data points of the same class to maintain their intrinsic neighbor relations, whereas neighboring points of different classes are no longer to stick to one an- other. Applying this assumption, an optimization problem weighting each feature is derived. The algorithm does not involve the dense matrix eigen-decomposition which can be computationally expensive in time. Extensive exper- iments are conducted to validate the significance of selected features using the Yale, Extended YaleB and PIE data- sets. The thorough evaluation shows that, using one-nearest neighbor classifier, the recognition rates using 100-- 500 leading features selected by the algorithm distinctively outperform those with features selected by the baseline feature selection algorithms, while using support vector machine features selected by the algorithm show less prominent improvement. Moreover, the experiments demonstrate that the proposed algorithm is particularly effi- cient for multi-class face recognition problem.     

基于数字全息的活体细胞动态相衬显微观察

针对生物活体细胞的观测要求,研究了一种基于数字全息的动态相衬显微实验方法.利用光纤器件和分立光学元件搭建了一套预放大离轴数字全息实验系统,采用无穷远校正显微物镜提高了成像分辨率,同时通过曲率匹配透镜和构造数字相位掩模对相位畸变进行了校正.对小鼠活体骨细胞样品进行了连续动态观察,得到了反映细胞运动和形态变化的相衬显微图像,证明了此方法的可行性.     

基于多波长同轴数字全息的相位恢复算法

同轴数字全息中固有的共轭像问题会严重影响再现像质量,已有的相位恢复算法需要大量计算才能祛除共轭像,且无法获得连续分布的解包裹相位像。提出一种基于多波长的相位恢复算法,该算法利用4个波长下记录的数字全息图,并在迭代过程中借助光学解包裹原理扩展了测量范围,实现了再现成像面中共轭像祛除的同时获得解包裹的相位分布。同时,由于在物面及记录面添加了约束条件,该方法中所用波长数少于其他已提出的基于多波长原理的相位恢复算法,而且具有更快的迭代收敛速度和更好的共轭像祛除效果。数值仿真和实验结果皆证明了该方法的有效性。      

医院信息管理系统的开发

医院信息管理系统庞大、复杂 ,目前我国医院信息系统大多只是实现其中的部分功能。本文通过对医院信息系统需求的分析 ,详细介绍了一个完整的针对中小型医院的管理信息系统的设计与实现 ,以及系统功能模块、网络拓扑结构及软件开发技术