A list-processing approach to compute Voronoi diagrams and theEuclidean distance transform

We propose an efficient Voronoi transform algorithm for constructing Voronoi diagrams using segment lists of rows. A significant feature of the algorithm is that it takes segments rather than pixels as the basic units to represent and propagate the nearest neighbor information. The segment lists are dynamically updated as they are scanned. A distance map can then be easily computed from the segment list representation of the Voronoi diagram. Experimental results have demonstrated its high efficiency. Extension of the algorithm to higher dimensions is also discussed     

基于多层结构中间件（EdbClient,EdbServer）的设计与实现

文中首先分析了Ｃｌｉｅｎｔ／Ｓｅｒｖｅｒｓ模型中中间件的应用背景。     

FPGA中的微程序设计

基于查表的商用ＦＰＧＡ是当前进行快速系统原型设计最流行的ＡＳＩＣ手段，文中根据ＸＩＬＩＮＸ的ＦＰＧＡ产品具有片上ＲＯＭ的特性，提出了在其内部实现微程序控制和管理复杂逻辑电路的新思想，并且在实际应用中取得满意的效果。文中还详细描述了在ＦＰＧＡ内部编写微程序的方法和编址技巧，给出了用ＦＰＧＡ实现一个典型的微程序控制器的电路模板，并总结了其应用特点和局限性。     

The Supervised Learning Gaussian Mixture Model

The traditional Gaussian Mixture Model(GMM)for pattern recognition is an unsupervised learning method.The parameters in the model are derived only by the training samples in one class without taking into account the effect of sample distributions of other classes,hence,its recognition accuracy is not ideal sometimes.This paper introduces an approach for estimating the parameters in GMM in a supervising way.The Supervised Learning Gaussian Mixture Model(SLGMM)improves the recognition accuracy of the GMM.An experimental example has shown its effectiveness.The experimental results have shown that the recognition accuracy derived by the approach is higher than those obtained by the Vector Quantization(VQ)approach,the Radial Basis Function (RBF) network model,the Learning Vector Quantization (LVQ) approach and the GMM.In addition,the training time of the approach is less than that of Multilayer Perceptrom(MLP).     

空间模型碰撞检测的向量符号分析方法与实现

用向量分析的方法从理论上对空间模型相互关系进行了探讨，定义了若干运算因子和表达公式，对３维物体模型间的相互碰撞检测问题进行了较深入的剖析，在此基础上给出了具体的算法。实验证明了本文算法的正确性和有效性。     

语音信号的预滤波和倒谱参数方差的统计

对于非实验室条件下的实时语音识别系统来说，能否准确提取出所需要的语音信号特征，是决定该识别系统正识率高低的关键因素之一，对语音信号进行预滤波以抑制噪音，有利于语音信号特征的提取，本文结合一个实际系统，讨论了其降噪问题，并建议以倒谱参数方差之统计特性是否符合一定规律的为标准，来衡量预滤波的效果，文中还对数字滤波器及随机低门限时域中心削波在预滤波中的作用进行了讨论，实验结果表明，预滤波取得了较好的效果     

传感器的真空循环注油法

根据实际要求和目前的注油方法及装置的情况，提出了真空循环注油的思想，设计并研制成功了这种注油装置；介绍了它的工作过程原理、特点及应用情况．     

数据通信技术纵览

随着社会信息化进程的深入,数据通信技术获得了长足的发展,论文对数据通信技术的发展进行了回顾,并对几种主要的数据通信技术进行了比较。     

Software support for multiprocessor latency measurement andevaluation

Parallel computing scalability evaluates the extent to which parallel programs and architectures can effectively utilize increasing numbers of processors. In this paper, we compare a group of existing scalability metrics and evaluation models with an experimental metric which uses network latency to measure and evaluate the scalability of parallel programs and architectures. To provide insight into dynamic system performance, we have developed an integrated software environment prototype for measuring and evaluating multiprocessor scalability performance, called Scale-Graph. Scale-Graph uses a graphical instrumentation monitor to collect, measure and analyze latency-related data, and to display scalability performance based on various program execution patterns. The graphical software tool is X-Windows based and is currently implemented on standard workstations to analyze performance data of the KSR-1, a hierarchical ring-based shared-memory architecture     

Combinations of weak classifiers

To obtain classification systems with both good generalization performance and efficiency in space and time, we propose a learning method based on combinations of weak classifiers, where weak classifiers are linear classifiers (perceptrons) which can do a little better than making random guesses. A randomized algorithm is proposed to find the weak classifiers. They are then combined through a majority vote. As demonstrated through systematic experiments, the method developed is able to obtain combinations of weak classifiers with good generalization performance and a fast training time on a variety of test problems and real applications. Theoretical analysis on one of the test problems investigated in our experiments provides insights on when and why the proposed method works. In particular, when the strength of weak classifiers is properly chosen, combinations of weak classifiers can achieve a good generalization performance with polynomial space- and time-complexity.