基于Elmore模型的Steiner树问题的求解

建立了一种求解基于Elmore延迟模型的Steiner树问题的遗传算法。针对Steiner树问题的特点,在引入一种新的具有自适应性的杂交概率和变异概率的基础上,提出了面向Steinet树问题的遺传算法和一种构造染色体的新方法。提供了遗传算法的结构并讨论了遗传算子。分析了基于时间和空间的算法复杂性。     

含有纯滞后对象的控制方法

评述纯滞后对象控制的两种典型方法─—大林算法和纯滞后补偿法的原理、优缺点、设计要求及存在问题，并讨论了两者的联系。     

周期信号的孔径抖动及其去除

孔径抖动是指模数转换器采样周期之间出现的相位抖动 ,是由各时钟周期边沿出现时刻的不确定性导致的。当输入信号频率较高时孔径抖动是模数转换器信噪比下降的一个重要原因。对数据采集系统中的孔径抖动进行了仿真实验 ,介绍了反卷积算法 ,并利用反卷积算法对周期信号的孔径抖动进行了去除。仿真结果表明该方法是有效可行的     

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.     

一种考虑补偿信用风险资本要求的算法

基于现行法定资本体制不考虑信用投资组合的多样化和限制空头信用风险头寸的补偿能力，设计了一种考虑补偿的信用风险资本要求的计算方法．该算法根据信用等级决定风险权重，可以更精确地测定信用风险资本．采用期限分段方法建立一个期间结构，区分当前和远期信用风险，考虑多头与空头信用风险头寸间的补偿．     

Petri网络在无控制交叉口延误分析中的应用

选用比较适合描述系统组织结构和动态行为的Petri网络模型对主路优先通行的无信号交叉口运行过程建立HSPN模型．在此基础上，结合间隙接受理论，对无控制交叉口进行平均延误分析探索，为交叉口仿真控制软件的研发奠定了算法基础。     

浅析"监督总体合格"与"监督抽查合格"

文章阐述了监督总体质量和监督抽查中的合格、不合格的涵义。     

基因技术对传统伦理道德的冲击

基因技术的发展使许多传统的伦理道德观念面临着挑战，文章将其主要归结为生命观、公平观和家庭观三个方面，并将基因技术对此三个方面的冲击加以分析。     

网络考试系统的安全设计

从对数据库系统的安全分析入手，结合网络考试系统的实际，从硬件系统、数据库系统、网络操作系统和网络应用程序几个方面，提出了解决网络考试系统安全性的方法。     

Subset threshold autoregression

We develop in this paper an efficient way to select the best subset threshold autoregressive model. The proposed method uses a stochastic search idea. Differing from most conventional approaches, our method does not require us to fix the delay or the threshold parameters in advance. By adopting the Markov chain Monte Carlo techniques, we can identify the best subset model from a very large of number of possible models, and at the same time estimate the unknown parameters. A simulation experiment shows that the method is very effective. In its application to the US unemployment rate, the stochastic search method successfully selects lag one as the time delay and five best models from more than 4000 choices. Copyright © 2003 John Wiley & Sons, Ltd.