人工免疫原理在网络入侵检测系统中的研究

文章分析了人工免疫系统的原理,简单建立了一种基于否定选择算法的网络入侵检测系统,引入了一种用于异常事件识别的r-字符块匹配规则,并对规则存在的漏洞进行了分析。     

高效的模式匹配算法研究

对入侵检测中模式匹配的方法进行了研究,分析了当前常用的模式匹配方法的弱点与不足,提出了一种基于三叉树结构的自动机方法,较好的避免了传统树型结构中由于节点数目变化而导致的不便。此外,利用匹配失败的信息,实现了跳跃匹配,提高了模式匹配的速度。*     

基于循环谱理论的BPSK直扩信号检测

研究了扩频信号的周期平稳性及其循环谱密度函数;在推导出BPSK扩频信号的循环谱密度函数的基础上,提出利用循环谱理论对BPSK直扩信号进行检测,并用MATLAB进行仿真验证。     

一种变步长D-Rake多用户检测器

在时变多径衰落信道下,接收到的CDMA信号功率变化较大,此时D-Rake盲自适应多用户检测器性能显著下降,将变步长LMS算法与基于主分量的相干合并引入到D-Rake(DecorrelatingRake)检测器中,构成一种变步长D-Rake,称之为VD-Rake(Variablestep-sizeDecorrelatingRake)检测器。该检测器能克服原D-Rake检测器对信号功率变化较敏感等缺点,有效地改善了D-Rake检测器的性能。     

催化重整装置进料/产物换热器泄漏的检测及判断

介绍了三种检测及判断催化重整装置进料/产物换热器泄漏的方法及原理,并在某工业装置上加以运用的情况.其中芳烃含量法是根据产物分离罐底物料和重整汽油芳烃含量变化来判断;转化率比较法是根据特定环烷烃的转化率来判断;示踪剂法是在原料中注入苯酚,再根据产物分离罐底物料中是否存在苯酚来判断.     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

受激布里渊光纤陀螺

介绍了受激布里渊光纤陀螺（B-FOG）的基本工作原理，简述了国内外B—FOG的研究现状、关键技术问题和解决方法，最后对B—FOG未来的发展状况进行了展望。     

有互感和电源的电容耦合电路的量子涨落

通过正则变换和幺正变换的方法研究了有互感和电源存在的情况下的介观电容耦合电路的量子涨落。结果表明电荷和电流的量子涨落与电源无关。当电路元件确定时，如果L1／L2的值很大或很小，耦合对涨落的影响很大。互感从有到无的过程中，回路1中电流的涨落和回路中2中电荷的涨落有明显的变化。换句话说，互感的有无对涨落的大小起着举足轻重的作用。     

一种新颖的基于非压缩数字视频的水印盲检测算法

数字水印是一种嵌入到多媒体数据中用来进行版权标识的工具。在众多的宿主媒体中，数字视频因具有隐藏容量大、透明性好、鲁棒性强等诸多优点而受到日益广泛的关注。但是很多文献中提到的视频水印都是从数据流中提取单帧图像进行处理，这类算法与静态图像的水印方法如出一辙，没有充分利用视频文件的各种特性。而且对帧平均、视频压缩等常见的运动图像攻击方法十分敏感。针对这些问题，本文以非压缩视频文件为实验对象，结合人类视觉模型和彩色图像场景分割的方法，提出并实现了一种基于视频时间轴的数字水印盲检测算法。实验结果表明算法有效实用。     

结合功率控制的时-空多用户检测器

针对CDMA系统中抗干扰技术,提出一种结合多用户检测、波束成形和功率控制的算法,对接收信号在时域和空间上进行联合处理,能大大抑制干扰,提高系统容量。