稳定性理论中的两个问题

本文讨论了吸引性与稳定性的关系,完善了稳定性的数学理论及应用一文中关于周期系统稳定与一致稳定等价的证明。     

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.     

叠片式小啮合角剃齿刀设计原理

本文介绍了小啮合角剃齿刀的设计原理和有关计算公式，并给出设计实例。按本文设计的叠片式小啮合角剃齿刀通用性好，有利于减少刀具库存。     

AC=BD在微分方程中的应用

利用AC＝BD的思想，将变系数广义KdV方程约化成常微分方程，求出了KdV方程的Lax对。     

太行山长城岭南山东北坡植被的研究

本文研究了太行山长城岭南山东北坡的植被分布及其特征。结果表明,从山麓至山顶,由于气候条件随海拨的逐渐升高而产生了明显的垂直变化,从而导致了植被分布的垂直变化。从山麓至山顶依次分布有落叶阔叶林、针阔混交林、针叶林和落叶阔叶灌丛等四个植被型、并因人为干扰落叶阔叶林正向针阔叶混交林和针叶林方向演替。     

高效凝胶渗透色谱测定硅油分子量及其分布

采用ＨＰＧＰＣ与蒸汽压渗透（ＶＰＯ）结合的方法研究了甲基苯基硅油等分子量及其分布测定方法。     

国内局部增氧助燃技术研究及应用进展

局部增氧助燃技术能用于各种燃料和大多数工业炉窑。介绍了局部增氧助燃技术的基本概念；然后通过国内有关典型应用实例说明：局部增氧助燃技术用于节能和环保时具有显著的综合效益；最后通过实测数据证明：用富氧助燃时，能明显降低燃料的燃点和燃尽温度，并大大缩短燃尽时间。     

1999—2001年《系统工程理论与实践》载文统计分析

对1999－2001年《系统工程理论与实践》所载论文从数量、内容、地区分布、系统分布和引文分布情况进行计量分析，各项统计结果显示，该杂志：1）载文信息量大，论文内容具有很强的导向和推动作用；2）期刊定位准确，具有独特的学术风格；3）作者体覆盖面广，但又集中于经济、科技较发达的地区；4）近期引文率高，载文内容新颖。     

Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-