基于NDIS Hook的网络数据包拦截和发送技术研究

结合实际项目经验,主要介绍了目前个人防火墙最为广泛使用的技术——NDIS Hook技术,重点探讨了如何使用NDIS Hook技术在NDIS层实现数据包的拦截与发送。     

Stabilization for nonlinear systems via a limited capacity communication channel with data packet dropout

This paper addresses the stabilization problem for a class of nonlinear systems. It is assumed that the controller can only receive the transmitted sequence of finite coded signals via a limited digital communication channel. Both state and output feedback coder-decoder-controller procedures are proposed. Stabilization conditions involving the size of coding alphabet, the sampling period, system state growth rate and data packet dropout rate are obtained. Finally, an example is given to illustrate the design procedures and effectiveness of the proposed results.     

多频段无线传感器网络实验平台构建

无线传感器网络作为一种新兴的技术具有广泛的研究价值和实际应用价值。设计并实现了一个多频段的无线传感器网络实验平台。该平台包括2.4GHz和433MHz的两个子网。两个子网分别通过网关与PC机相连,PC机完成对不同子网的数据包分析和解包,并可对各子网下达指令。实验结果表明,该平台能够完成胜任一般实验的需求,对于理论研究和实际应用都具有十分重要的意义。     

网络心跳包序列的数据流分簇检测方法

在对网络会话进行时序分析的基础上,提出基于数据流分簇处理的心跳包序列检测方法。对数据流进行时序分簇处理,按周期性特征扩充簇集合,筛除不符合特征的簇对象,根据稳定的簇集合检测心跳包序列。实验结果表明,该方法检测率较高、误检率较低,能够实现实时检测和处理。     

一种改进的数据通信协议设计与实现

在主机与目标机间建立与通信端口无关的命令驱动式数据通信协议,给出数据包格式及命令功能定义。该协议采用分层和模块化设计方法,支持1553B和RS-232 2种通信端口,通过扩展底层通信管理模块可实现对CAN、SPI、SPACEWIRE等总线的支持。SPARC V8存储器加载和下载软件的运行结果验证该协议的正确性,表明其能屏蔽不同通信端口之间的差异性,实现正常的数据传输。     

Case-based expert system using wavelet packet transform and kernel-based feature manipulation for engine ignition system diagnosis

Whenever there is any fault in an automotive engine ignition system or changes of an engine condition, an automotive mechanic can conventionally perform an analysis on the ignition pattern of the engine to examine symptoms, based on specific domain knowledge (domain features of an ignition pattern). In this paper, case-based reasoning (CBR) approach is presented to help solve human diagnosis problem using not only the domain features but also the extracted features of signals captured using a computer-linked automotive scope meter. CBR expert system has the advantage that it provides user with multiple possible diagnoses, instead of a single most probable diagnosis provided by traditional network-based classifiers such as multi-layer perceptions (MLP) and support vector machines (SVM). In addition, CBR overcomes the problem of incremental and decremental knowledge update as required by both MLP and SVM. Although CBR is effective, its application for high dimensional domains is inefficient because every instance in a case library must be compared during reasoning. To overcome this inefficiency, a combination of preprocessing methods, such as wavelet packet transforms (WPT), kernel principal component analysis (KPCA) and kernel K-means (KKM) is proposed. Considering the ignition signals captured by a scope meter are very similar, WPT is used for feature extraction so that the ignition signals can be compared with the extracted features. However, there exist many redundant points in the extracted features, which may degrade the diagnosis performance. Therefore, KPCA is employed to perform a dimension reduction. In addition, the number of cases in a case library can be controlled through clustering; KKM is adopted for this purpose. In this paper, several diagnosis methods are also used for comparison including MLP, SVM and CBR. Experimental results showed that CBR using WPT and KKM generated the highest accuracy and fitted better the requirements of the expert system.     

Structure damage diagnosis using neural network and feature fusion

A structure damage diagnosis method combining the wavelet packet decomposition, multi-sensor feature fusion theory and neural network pattern classification was presented. Firstly, vibration signals gathered from sensors were decomposed using orthogonal wavelet. Secondly, the relative energy of decomposed frequency band was calculated. Thirdly, the input feature vectors of neural network classifier were built by fusing wavelet packet relative energy distribution of these sensors. Finally, with the trained classifier, damage diagnosis and assessment was realized. The result indicates that, a much more precise and reliable diagnosis information is obtained and the diagnosis accuracy is improved as well.     

结合听觉掩蔽效应的时频自适应小波阈值增强

针对浊音、清音和噪声的不同特性,结合听觉掩蔽并使用随尺度变化的多阈值对语音信号进行处理.提出了多小波门限估计法,该方法针对不同声音成分,使用不同的与尺度有关的缩小因子调节门限值;通过估计各频带内的信噪比,实现了阈值的时频自适应变化;用巴克小波包分解法模拟人耳临界带特性,用小波谱减法对带噪语音进行预增强,采用Johnst...     

网络化最优预测状态估计

当网络诱导时延和数据包丢失确定可知时,提出了一种网络化最优预测状态估计器设计方法,能够补偿网络诱导时延和数据包丢失对估计性能的影响,理论分析表明了随着网络诱导时延或数据包丢失的增加,该估计器在获得明显补偿效果的同时预测估计偏差略微递增,并给出了估计系统的稳定性条件,最后通过仿真和实验验证了所提出方法的有效性和理论分析的正确性.     

具有数据包丢失及转移概率部分未知的网络控制系统H∞控制

研究一类具有数据包丢失及状态转移概率部分未知的网络控制系统随机稳定性及H∞控制问题．传感器与控制器之间、控制器与执行器之间存在数据包丢失的网络控制系统被建模成具有4个子系统的跳变系统,4个子系统之间的跳变遵行Markov跳变过程,并具有部分未知的跳变概率．利用Lyapunov稳定性定理及线性矩阵不等式的求解方法得到该类系统随机稳定的充分条件,并给出了相应的∞状态反馈控制器的设计方法．数值仿真结果验证了本文方法的正确性和有效性．