声表面波滤波器的匹配电路设计

介绍了通过测试仪器采集的声表面波（SAW）滤波器的Sij(i,j=1,2）参数来优化匹配电路的方法。首先将采集的Sij(i,j=1,2）参数转换为SAW滤波器Yij(i,j=1,2）参数，然后建立新的S12（或S21）参数与匹配电路的依赖关系，通过优化匹配电路元件值，而使滤波器的插入损耗和通带波动满足目标值，该方法的主要优点是考虑整个通带特性，而不是考虑通带内的某一点（如中心频率）。     

基于运动矢量的视频图象数字水印算法

数字水印技术是近年发展起来的一种用于数字产品版权保护和真伪性论证的新兴技术。与静止图象相比，视频水印技术要满足盲检的要求。本文根据运动矢量的特征值ρl，提出了一种视频图象水印新算法。实验结果表明，所提出的水印算法简单、快速，能满足视频编码的实时性要求；算法与现有的视频压缩标准有很好的兼容性；水印的提取具有盲检功能，无需原图象；水印的嵌入不影响I帧的图象质量，与嵌入水印前的原压缩图象相比，嵌入水印后的视频图象信噪比损失很小。     

指纹细节特征提取与剪枝

指纹图像经预处理后，由于各种原因，会产生数以百计的特征。为了图像匹配的精确和快速，提出一套在细化后的指纹点线图上提取细节特征并对其剪枝的方法，并根据细节特征的拓扑特性，设计了验证其可靠性的算法。通过实验，证明了该后处理过程在去除指纹图像伪特征方法面具有良好的效果。     

Cluster analysis in industrial market segmentation through artificial neural network

Market segmentation has commonly applied cluster analysis. This study intends to make the comparison of conventional two-stage method with proposed two-stage method through the simulated data. The proposed two-stage method is the combination of self-organizing feature maps and K-means method. The simulation results show that the proposed scheme is better than the conventional two-stage method based on the rate of misclassification.     

多棒高功率固体激光器动态模匹配研究

采用光学矩阵分析了多元热透镜谐振腔内模式的动态匹配特征,给出了平平腔参数调整的关系式,实验结果与理论分析相符,并在两棒连续Nd:YAG系统上得到0W～530W功率范围的稳定输出.     

快速星图匹配算法的研究

将态敏感和姿态稳定是卫星的重要技术之一。星体敏感器是目前最高精度的姿态测量技术。对于这种技术，很多文献都进行了讨论，并涌现了许多关于星图匹配行之有效的算法。     

浅谈抽水蓄能电站的特点及其优越性

本文介绍了国外抽水蓄能电站的发展过程与现状，修建抽水蓄能电站的八大优点。为了改善我省电力系统的运行条件，提出了在我省修建抽水蓄能电站的四点建议。     

语音识别算法的确定与实现

在语音识别的实验中，对几种算法方案进行了比较、分析和择优淘劣，标准是在一定词汇量的条件下，权衡占用机器的内存空间、（正确）识别率和响应速度。力争使与话者有关的单词语音识别系统的设计达到优化，取得满意的结果。本文即是此项实验的总结。     

角调谐飞秒同步泵浦KTP红外光参量振荡器

用平均输出功率为１．１Ｗ，脉宽为９０ｆｓ的商用再生锁模Ｔｉ：Ｓａｐｐｈｉｒｅ激光器作为泵浦源，用ＫＴＰ作为非线性光学介质，制成一台同步泵浦飞秒光学参量振荡器。其输出调谐范围为１．０４μｍ至１．２６μｍ，平均输出功率在１００ｍｗ左右，脉宽仅约１００ｆｓ。     

Successive pattern classification based on test feature classifier and its application to defect image classification

A novel successive learning algorithm based on a Test Feature Classifier is proposed for efficient handling of sequentially provided training data. The fundamental characteristics of the successive learning are considered. In the learning, after recognition of a set of unknown data by a classifier, they are fed into the classifier in order to obtain a modified performance. An efficient algorithm is proposed for the incremental definition of prime tests which are irreducible combinations of features and capable of classifying training patterns into correct classes. Four strategies for addition of training patterns are investigated with respect to their precision and performance using real pattern data. A real-world problem of classification of defects on wafer images has been dealt with by the proposed classifier, obtaining excellent performance even through efficient addition strategies.