现多重周期序列联合2-adic复杂度的稳定性

该文首次提出了联合k-错2-adic复杂度的概念,并与联合k-错2-adic复杂度一齐作为衡量多重周期序列联合2-adic复杂度稳定性的指标。随后分别研究了两种联合错2-adic复杂度意义下的序列计数问题以及满足2N-1=p,p1p2的周期为N的m重序列联合错2-adic复杂度数学期望的下界并说明了不存在2N-1=pe(e1),的情况。该文的结果对于研究多重周期序列联合2-adic复杂度的稳定性有重要意义。     

广义自缩序列的线性复杂度

周期与线性复杂度的稳定性是衡量周期序列伪随机性质的一个重要指标.本文在给出广义自缩序列的线性复杂度的上界之后,借助伽罗瓦域中的若干理论,分析了该类序列的线性复杂度的稳定性,包括广义自缩序列在单符号插入、删除变换和少量符号替换操作下的线性复杂度的变化情况,给出了变化后序列的线性复杂度的具体表达式.     

Fp上pn-周期序列的1-错线性复杂度

周期序列的线性复杂度和k-错线性复杂度是衡量密钥流序列随机性的两个重要指标.该文给出了Fp上pn-周期的序列所有可能的1-错线件复杂度的值以及具有给定1-错线性复杂度的序列个数.更进一步,该文给出了Fp上pn-周期的序列1-错线性复杂度的期望.     

随机周期序列☆错线性复杂度的期望上界

周期序列的k错线性复杂度是衡量流密码系统的安全性能的一个重要指标。本文给出了周期序列k错线性复杂度上界的一个更强的结果,从而给出了几种不同情形下随机周期序列k错线性复杂度的期望的上界。特别地,还给出了周期N=pv,随机周期序列满足一定条件时1错线性复杂度的期望更紧的结果。     

基于不同路由协议的Ad hoc网络控制仿真研究

基于Ad hoc中经典的AODV(Ad hoc按需距离矢量路由协议)和DSDV(目的序列距离矢量路由协议)两种路由协议,文章选取了对控制系统性能影响很大的时延、丢包率、控制稳定性等参数来做比较,分析了基于两个协议的控制性能。通过NS的仿真得出了在网络规模不大的情况下,AODV协议相比于DSDV协议来说,更适合进行网络控制,其稳定性更高,并且在网络拓扑变化激烈的情况下,控制系统稳定性差距更加明显。     

多周期伪随机序列扩散体近场接收点的优化选择

在远场条件下,伪随机序列扩散体具有良好的扩散特性。多周期的伪随机序列扩散体越来越多地应用在各种小型房间里,接收点到多周期伪随机序列扩散体的距离并不满足远场条件。根据基尔霍夫衍射理论,研究了扩散频率范围内接收点在近场时多周期伪随机序列扩散体的极性响应,并与平板进行了比较和分析,总结出表征扩散性能变化的过渡距离。实际使用时要适当选择接收点距离,使既能获得良好的扩散效果,又能保证一定的声压级。     

几种流密码研究的母函数方法

本文利用母函数的方法对几种经常用到的特殊的流密码周期序列的补序列,周期序列的部分和序列,逆向序列和有限生成序列进行了研究,给出了它们的极小多项式,周期和母函数。对有限生成序列讨论了线性复杂度变化情况和联结多项式次数不变的情况下两个生成序列之间的关系。     

一类理想自相关序列的伪随机性

伪随机序列在流密码、信道编码、扩频通信等领域有着广泛的应用.线性复杂度及其稳定性是序列伪随机性的重要度量指标.C Ding等给出了一类具有理想自相关性的周期序列,该序列的0-1分布是几乎均衡的.本文讨论了此类序列的其它伪随机性.本文的主要结果如下:此类序列具有令人满意的线性复杂度;在一个符号替换之下此类序列的线性复杂度不会退化.     

超宽带穿墙探测雷达TH-UWB脉冲串信号分析

从定义出发推导了跳时调制超宽带广义高斯脉冲串(GGP)波形距离模糊函数的解析表达式,并通过仿真分析该波形模糊函数与跳时序列自相关特性、序列周期、脉冲平均重复周期、有效时间宽度、时间尺度因子及调制系数的关系.结果表明:选择良好自相关特性和较长序列周期的跳时序列可增强旁瓣抑制能力;增大时间尺度因子或减小有效时间宽度可增加距离分辨力;权衡选择适宜的调制系数不仅保持波形原有的距离分辨特性,而且有利于采用距离门技术抑制旁瓣.     

2mpn周期二元序列的线性复杂度和k错线性复杂度

序列线性复杂度的稳定性是衡量其随机性好坏的一个重要指标.针对2mpn周期二元序列,利用多项式分解等工具,确定了使得序列的k错线性复杂度严格小于其线性复杂度的最小k值的上下界,其中n是正整数,m是非负整数,P是奇素数,2是模p2的原根.     

Tracking pylorus in ultrasonic image sequences with edge-based optical flow

Tracking pylorus in ultrasonic image sequences is an important step in the analysis of duodenogastric reflux (DGR). We propose a joint prediction and segmentation method (JPS) which combines optical flow with active contour to track pylorus. The goal of the proposed method is to improve the pyloric tracking accuracy by taking account of not only the connection information among edge points but also the spatio-temporal information among consecutive frames. The proposed method is compared with other four tracking methods by using both synthetic and real ultrasonic image sequences. Several numerical indexes: Hausdorff distance (HD), average distance (AD), mean edge distance (MED), and edge curvature (EC) have been calculated to evaluate the performance of each method. JPS achieves the minimum distance metrics (HD, AD, and MED) and a smaller EC. The experimental results indicate that JPS gives a better tracking performance than others by the best agreement with the gold curves while keeping the smoothness of the result.     

基于距离、角度、模板的角点检测算法

提出了一种基于距离、角度序列极值和距离模板匹配的角点检测算法。此算法不但与 基于灰度和基于曲率的方法截然不同,而且克服了他们的缺点。首先利用距离、角度序列极值检测得到明显转折部位的角点,然后根据距离模板匹配获得转折平稳部位的角点,最后经过伪角点删除,得到最终结果。仿真实验表明,该算法通过对序列极值判断支撑区域及模板大小的控制,抑制了数字化误差及噪声的影响,可以有效地实现二维图像的角点检测与定位,具有较高的精度,是一种实用、有效的角点探测算法。     

Human action recognition using Pose-based discriminant embedding

Manifold learning is an efficient approach for recognizing human actions. Most of the previous embedding methods are learned based on the distances between frames as data points. Thus they may be efficient in the frame recognition framework, but they will not guarantee to give optimum results when sequences are to be classified as in the case of action recognition in which temporal constraints convey important information. In the sequence recognition framework, sequences are compared based on the distances defined between sets of points. Among them Spatio-temporal Correlation Distance (SCD) is an efficient measure for comparing ordered sequences. In this paper we propose a novel embedding which is optimum in the sequence recognition framework based on SCD as the distance measure. Specifically, the proposed embedding minimizes the sum of the distances between intra-class sequences while seeking to maximize the sum of distances between inter-class points. Action sequences are represented by key poses chosen equidistantly from one action period. The action period is computed by a modified correlation-based method. Action recognition is achieved by comparing the projected sequences in the low-dimensional subspace using SCD or Hausdorff distance in a nearest neighbor framework. Several experiments are carried out on three popular datasets. The method is shown not only to classify the actions efficiently obtaining results comparable to the state of the art on all datasets, but also to be robust to additive noise and tolerant to occlusion, deformation and change in view point. Moreover, the method outperforms other classical dimension reduction techniques and performs faster by choosing less number of postures.     

序列k-错线性复杂度算法

本文给出了一个测量流密码序列稳定性的重要指标Ｋ－错线性复杂度的算法,即求ＧＦ（ｑ）上（ｑ＝ｐ＾ｍ,ｐ：素数）周期为Ｎ＝ｐ＾ｎ序列的Ｋ－错线性复杂度的快速算法。在这里对广义ＧａｍｅｓＣｈａｎ算法－ＧＦ（ｑ）上ｐ＾ｎ序列线性复杂度算法进行了简化,并给出了ＧＦ（ｑ）上ｐ＾ｎ序列Ｋ－错线性复杂度算法及其证明。     

一种延长DVI高清视频信号传输距离的方法

针对DVI高清视频传输距离短的问题,提出了一种利用千兆以太网物理层协议进行点对点低延时传输的方法。该方法通过对DVI视频的采集,并通过一种改进的低复杂度压缩算法,压缩后的数据利用千兆以太网底层协议的ARP包承载数据传输,从而实现实时点对点传输。用此方法可使高清DVI信号延长传输到100 m以上,满足了工程中对高清视频远程实时监控的要求。     

Comma free error correcting codes of variable length, generated by finite-state encoders

A finite-state code (FSC) is the set of output sequences of a finite-state encoder. The case is considered where the period of the eneoder is one and the code is used as an error-correcting code. In this context the Levenshtein distance will measure the discrepancy between an information sequence and its estimate, and the minimum Hamming distance will be taken as the criterion of efficiency. The class of binary autocomplementary FSC's (BAC's) satisfies a lower bound on the minimum Hamming distance that is essentially equivalent to the well-known Gilbert bound for block codes. Examples of good BAC's are provided in the last section.     

结合预确定距离的BIST测试矢量优化

在分析和介绍了海明距离与笛卡尔距离的基础上,通过改进细胞自动机生成的测试矢量间的链接性,提出了结合预确定距离的测试矢量优化方法.该方法通过设计最大海明距离和笛卡尔距离构造预确定距离序列,并利用遗传算法的全局寻优得到最佳预确定测试序列.通过ISCSA’85实验结果表明,该方法生成的预确定测试矢量比LFSR-CA结构的测试方法有更高的故障覆盖率和测试效率,在检测难测故障中效果更明显.     

An adaptive learning rate GMM for background extraction

The rapidness and stability of background extraction from image sequences are incompatible, that is, when a conventional Gaussian mixture models （GMM）is used to rebuild the background, if the background regions of the scene are changed, the extracted background becomes bad until the transition is over. A novel adaptive method is presented to adjust the learning rate of GMM in a Hilbert space. The background extraction is treated as a process of approaching to a certain point in the Hilbert space, so the real-time learning rate can be obtained by calculating the distance between the two adjacent extracted background images, and a judgment method of the stability of background is got too. Compared with conventional GMM, the method has both high rapidness and good stability at the same time, and it can adjust the learning rate online. The experiment shows that it is better than conventional GMM, especially in the transition process of background extraction.     

一种基于WG序列的测距新方法

应用具有良好相关特性的伪随机序列可以提高雷达测距信噪比，有助于实现高效率低功率的目标探测。二相发射态结合雷达的非发射状态可以定义三态序列。文中介绍了三态序列的一些概念及其主要性质；讨论了Wolfmann-Goutelard(WG)序列的近完美周期自相关性；并基于三态序列相关函数的定义，应用WG序列生成的三态码^3WG,构造了一种适用于测距雷达的，具有良好性质的码序列测距方法。该方法可以替代m序列在测距中的作用。