一种用于岩心序列图像轮廓提取的改进Snake算法

针对岩心序列图像的轮廓提取,提出了一种改进的Snake算法。对序列图像第1帧手动初始化轮廓点,如果相邻轮廓点之间距离大于给定阈值,则自动插入新的点,对于每一轮廓点,按照一定规则计算其搜索半径,然后找出搜索半径内的能量最小的点代替原始点。前一帧得到的结果又作为后一帧的初始点进行轮廓提取,从而得到整个序列图像的轮廓。实验结果表明,本算法具有简单、实用、实时性强等特点。     

基于最小自由度优先原则的任意多边形模块布局算法

给出了直角多边形模块自由度的定义和公式,扩展了最小自由度优先原则,使算法能够处理任意直角多边形模块以及有相对约束的模块.实验结果说明该方法在布局效果和效率上都有良好的表现.     

Distributed Construction of Connected Dominating Set in Wireless Ad Hoc Networks

Connected dominating set (CDS) has been proposed as virtual backbone or spine of wireless ad hoc networks. Three distributed approximation algorithms have been proposed in the literature for minimum CDS. In this paper, we first reinvestigate their performances. None of these algorithms have constant approximation factors. Thus these algorithms cannot guarantee to generate a CDS of small size. Their message complexities can be as high as O(n ²), and their time complexities may also be as large as O(n ²) and O(n ³). We then present our own distributed algorithm that outperforms the existing algorithms. This algorithm has an approximation factor of at most 8, O(n) time complexity and O(nlogn) message complexity. By establishing the (nlogn) lower bound on the message complexity of any distributed algorithm for nontrivial CDS, our algorithm is thus message-optimal.     

Fault Attack on a Point Blinding Countermeasure of Pairing Algorithms

Recently, Page and Vercauteren proposed a fault attack on pairing algorithms and two countermeasures against such an attack. The countermeasure uses either a random scalar or a random point to blind the input points. To defeat the countermeasure using a random point, we utilize the point addition formula on an elliptic curve. As a result, we successfully defeat the countermeasure using a random point.     

移动通信中基于智能天线的抗多径干扰技术

本文首先概述了多径信道传输特性,在此基础上,重点讨论了基于智能天线抗多径干扰技术的理论,并对基于ＣＭＡ算法的智能天线抑制多径干扰进行了计算机仿真。     

光接入网在惠州本地电信网中的应用

本文介绍了惠州市光接入网的建设现状 ,并讨论了目前存在的一些问题以及采取的原则与策略。     

基于改进遗传神经网络模型的通信网络故障识别和告警相关性分析方法

随着通信网络自身规模、带宽和复杂度的不断增加以及用户对网络服务质量要求的不断提高,迫切需要智能化的网络管理系统对当今高速通信网络进行有效和可靠的管理,而故障管理正在变的比以往任何时候都更加困难和重要。当网络产生某一故障或失效时,往往在短时间内产生成千上万个告警信息,因而分析这些告警的相关性也变得更加复杂。现有的一些告警分析系统均在不同程度上存在可扩充能力差,难于应付复杂局面,缺乏学习能力等不足。本文提出了一种基于改进遗传神经网络模型的故障识别和告警相关性分析方法。实验表明,这种方法可克服一般告警相关性分析方法的局限,不仅简单,而且在网络学习和训练效率上也高于传统的BP算法,标准遗传算法和一般的自适应遗传算法。     

基于CMA算法的自适应阵的初始化研究

在多径传播和其它同频干扰存在而同时接收到多个恒模信号时,若已知需要信号到达方向的通信条件下,本文提出了恒模算法的初始预测方法,对干扰起到了零陷作用,数字模拟结果表明了这一初始预测方法是有效的。     

流水线阵列乘法器的功耗分析和优化

针对流水线结构阵列乘法器，分别采用寄存器翻转统计和门级翻转率统计的方法进行了功耗分析，创新地提出了一种通过增加判断逻辑进行数据预分流以实现功耗优化的方法。实验结果证明，这种优化方法能够带来明显的功耗节省。类似方法也可普遍用于逻辑行为对称但实现结构不对称的数据通路单元的低功耗设计实现中。     

A robust adaptive weighted constant modulus algorithm for blind equalization of wireless communications systems under impulsive noise environment

A robust adaptive weighted constant modulus algorithm is proposed for blind equalization of wireless communication systems under impulsive noise environment. The influence of the impulsive noise is analyzed based on numerical analysis method. Then an adaptive weighted constant modulus algorithm is constructed to adaptively suppress impulsive noise. Theoretical analysis is provided to illustrate that the proposed algorithm has a robust equalization performance since the impulsive noise is adaptively suppressed. Moreover, the proposed algorithm has stable and quick convergence due to avoidance of large misadjuntment and adoption of large step size. Simulation results are presented to show the robust equalization performance and the fast convergence speed of the proposed algorithm under both impulsive noise and Gaussian noise environments.