SNORT规则匹配算法改进

检测引擎作为入侵检测系统(IDS)的核心模块,基本上采用基于模式匹配的检测方法,选择设计1个好的模式匹配算法对入侵检测系统的性能至关重要。对SNORT的原有规则匹配算法bm进行改进,在改进规则匹配算法中,将具有相同前缀的规则生成1棵规则树,在规则匹配的过程中将数据包内容和规则树进行匹配,在匹配时,可以和多个规则同时进行,大大减少了在规则匹配中花费的时间,从而提高了SNORT的性能。改进后的系统和原来系统进行了几种测试,通过测试改进后的系统比原来的系统速度明显提高。在流量大的情况,丢包情况也减少了。     

识别混凝土板内部缺陷的人工神经网络算法

以一维有缺陷混凝土板为研究对象，分别采用Leverberg-Marcluardt和径向基神经网络算法，对缺陷的深度与厚度进行识别，从而实现对混凝土板内部缺陷的三维重构，称为红外CT模拟．两类神经网络算法的识别结果表明：Leverberg-Marcluardt神经网络较径向基神经网络具有更好的收敛精度与计算效率．     

复杂背景下低信噪比点目标的实时检测算法及实现

为检测复杂背景中的低信噪比 (SNR)点目标 ,提出了一种局部自适应门限检测算法。该算法以低通滤波算法估计背景中的低频成分 ,及图像局部方差估计背景起伏 ,来计算出局部自适应的目标检测判决门限。该算法充分考虑了可实现性和实时性并采用现场可编程门阵列 (FPGA)设计实现该算法。理论分析和试验结果都表明 ,该算法可有效抑制云层、树木、地物等背景杂波、检测出复杂背景下的低信噪比点目标 ,具有恒虚警率和易于工程实现的优点。     

热轧圆钢外径的激光在线检测研讨

本文报导热轧圆钢激光在线检测外径的阶段性研究结果，给出仪器研制原理及光机结构设计同仪器精度关系的研讨．     

一种基于数字水印的错误检测和定位技术

为了增强视频通信系统在有误码信道的适应能力 ,提出了一种基于数字水印技术的错误检测方法 ,使得解码器可以对误码块进行有效的补偿。其原理为编码器在量化后离散余弦变换 (DCT)系数中嵌入易碎的数字水印 ,解码器可以通过提取水印从而确认错误以及错误发生的首宏块位置。仿真结果证明 :在信道误码率为 5× 10 - 4时 ,与常用的基于语法的方法相比 ,本方法的错误检测率是其的 1.32～ 1.82倍 ,错误正确定位率是其的 2 .95～ 5 .32倍 ,而且 PSNR只有微弱降低 ,同时算法复杂度很低     

The General Machining Process Simulator GMPS

Ｔｈｅ　Ｇｅｎｅｒａｌ　Ｍａｃｈｉｎｉｎｇ　Ｐｒｏｃｅｓｓ　Ｓｉｍｕｌａｔｏｒ　ＧＭＰＳＸｉａｏＴｉａｎｙｕａｎ，ＹａｎｇＧａｎｇ＆ＬｉＸｉｎ（ＤｅｐａｒｔｍｅｎｔｏｆＡｕｔｏｍａｔｉｏｎ，ＴｓｉｎｇｈｕａＵｎｉｖｅｒｓｉｔｙ，Ｂｅｉｊｉｎｇ，Ｃｈｉ...     

量子搜索与两体弹性碰撞过程的相似性

量子搜索问题是由Grover首先提出的,其核心是利用量子相干性加速搜索过程[1].量子系统在外部条件和内部作用下演化,使待搜索本征态的系数接近于1,其他本征态的系数接近于0.通过对量子搜索过程的研究,我们发现了量子搜索与经典力学中两体弹性碰撞过程的相似性.利用这种相似性,可以讨论量子搜索的内在本质以及相关的问题.     

The detection of structural deformation errors in attitude determination

In the determination of the attitude parameters from a multi-antenna GPS array, one of the major assumptions is that the body frame is rigid at all times. If this assumption is not true then the derived attitude parameters will be in error. It is well known that in airborne platforms the wings often experience some displacement during flight, especially during periods of initializing maneouvres, such as taking off, landing,and banking. Often it is at these points in time that it is most critical to have the most precise attitude parameters.There are a number of techniques available for the detection of modeling errors.The CUSUM algorithm has successfully been implemented in the past to detect small persistent changes. In this paper the authors investigate different methods of generating the residuals, to be tested by the CUSUM algorithm, in an effort to determine which technique is best suited for the detection of structural deformation of an airborne platform. The methods investigated include monitoring the mean of the residuals generated from the difference between the known body frame coordinates, and those calculated from the derived attitude parameters. The generated residuals are then passed to a CUSUM algorithm to detect any small persistent changes. An alternative method involves transforming the generated residuals into the frequency domain through the use of the Fast Fourier Transform. The CUSUM algorithm is then used to detect any frequency changes. The final technique investigated involves transforming the generated residuals using the Haar wavelet. The wavelet coefficients are then monitored by the CUSUM algorithm in order to detect any significant change to the rigidity of the body frame.Detecting structural deformation, and quantifying the degree of deformation, during flight will ensure that these effects can be removed from the system, thus ensuring the most precise and reliable attitude parameter solutions. This paper, through a series ofsimulations, will assess the effectiveness of the above mentioned techniques for detecting structural deformation effects on a GPS multi-antenna array. These principles are then tested with experimental data.     

小波多尺度分解及其在SAR图象目标检测中的应用

合成孔径雷达图象的目标检测是最重要的任务之一.目前用于目标检测的现有方法速度较慢、准确率较低、精度较差.作者提出小波分解的方法用于目标检测.同尺度目标检测采用二维离散二进小波分解方法,提高检测速度.不同尺度的目标检测采用多尺度二维离散小波分解方法,提高检测准确率.图象匹配采用灰度归一化的灰度相关匹配方法,提高匹配精度.实验证明,采用该法进行目标检测能获得较好的效果.