手持导航设备的电磁干扰定位和整改

手持导航产品中,电磁干扰对产品性能的影响巨大。该文重点描述PND产品中EMI定位和整改问题的一般分析方法和手段,即通过组合使用通用的电、磁场探头,GPS有源天线,电压探头进行近场扫描,准确定位PND中的干扰源和干扰路径,并举例说明这些方法的应用。     

事务存储中的一种自适应冲突检测算法

事务存储被认为是极具前景的多核处理器并行编程的手段,但存在开销过大的问题。采用Bloom Filter对事务间访问共享变量进行冲突检测,能够有效地降低开销,但其存在误判会导致不必要的事务作废,因此要尽可能减少。简要介绍了Bloom Filter和事务存储,提出了一种事务存储的自适应冲突检测算法ACDA,根据事务读写集合大小自适应地调整Bloom Filter的位串大小,在较低开销的情况下,保持误判率不增加。分析了软件事务存储中实现ACDA的特点,初步实现ACDA,与主流软件事务存储实现RSTM相比,在事务存储测试程序STAMP中,开销可接受的前提下,减少因误判而作废的事务最高达93%。给出了对ACDA哈希函数进一步优化的思路。     

Delta算子描述的离散系统故障检测滤波器

研究基于Delta算子模型的离散时间系统故障检测问题.推导了Delta算子系统的故障可检测和可分离条件,给出了Delta算子模型的故障检测滤波器设计方法.研究表明,在采样周期很小时,Delta算子故障检测趋近于连续模型的相应结果,可统一处理连续系统和离散系统故障检测的相关问题.仿真实例验证了该方法的有效性.     

基于卡尔曼滤波的木材含水率在线估计

为解决木材干燥过程木材含水率检测精度低的问题,提高木材干燥的自动控制水平,针对以含水率为基准的干燥过程,提出了应用卡尔曼滤波进行木材含水率在线估计方法。为验证该方法的有效性：首先建立了基于含水率基准加入高斯噪声数据集的卡尔曼估计模型,并在此模型基础上对实验测得的数值进行了在线估计和比较,结果表明卡尔曼滤波方法具有较好的估计精度。     

一种彩色图像去噪的快速PGF滤波算法

提出了一种去除彩色图像噪声的快速PGF滤波算法.首先介绍了基本的PGF滤波算法,然后在分析PGF滤波算法的基础上,提出了一种简化的PGF滤波算法.最后,对该算法进行了仿真研究,仿真结果表明该算法在完成图像的噪声平滑和边缘保持的同时实现了图像的快速滤波.     

使用Acegi安全框架轻松保护Web程序

利用Acegi安全框架实现对Web程序的保护,从其独特的过滤器机制入手,结合典型处理过程,探讨了Acegi的身份验证与授权的内部管理器机制;分析了Web特定环境下安全拦截器强制安全保护与授权处理器的登录处理,轻松完成了系统的安全性要求。     

自动选取特征的行人跟踪

根据非刚性物体运动的特点,提出一种利用支持向量机有效对多目标进行分离并能自动选择目标最明显特性区域的覆盖比算法,克服了以往对选取区域事先进行设定的情形。采用目前常用的加权颜色直方图作为备选粒子,进行行人跟踪。由于建立了合理目标颜色模型,减少了对粒子数量的需求,降低了计算复杂度,有利于实现实时跟踪。利用Bhattacharyya距离描述粒子与目标颜色模型的相似性,作为粒子更新权值的依据。试验结果证明了自动选取被跟踪目标的特征与事先设定备选区域有等价效果。     

A simple decision tree-based disturbance monitoring system for VSC-based HVDC transmission link integrating a DFIG wind farm

Fault detection and classification is a key challenge for the protection of High Voltage DC (HVDC) transmission lines. In this paper, the Teager–Kaiser Energy Operator (TKEO) algorithm associated with a decision tree-based fault classi f ier is proposed to detect and classify various DC faults. The Change Identification Filter is applied to the average and differential current components, to detect the first instant of fault occurrence (above threshold) and register a Change Identified Point (CIP). Further, if a CIP is registered for a positive or negative line, only three samples of currents (i.e., CIP and each side of CIP) are sent to the proposed TKEO algorithm, which produces their respective 8 indices through which the, fault can be detected along with its classification. The new approach enables quicker detection allowing utility grids to be restored as soon as possible. This novel approach also reduces computing complexity and the time required to identify faults with classification. The importance and accuracy of the proposed scheme are also thor oughly tested and compared with other methods for various faults on HVDC transmission lines.     

Analogue VLSI primitives for perceptual tasks in machine vision

A variety of computational tasks in early vision can be formulated through lattice networks. The cooperative action of these networks depends upon the topology of interconnections, both feedforward and recurrent ones. The Gabor-like impulse response of a 2nd-order lattice network (i.e. with nearest and next-to-nearest interconnections) is analysed in detail, pointing out how a near-optimal filtering behaviour in space and frequency domains can be achieved through excitatory/inhibitory interactions without impairing the stability of the system. These architectures can be mapped, very efficiently at transistor level, on VLSI structures operating as analogue perceptual engines. The hardware implementation of early vision tasks can, indeed, be tackled by combining these perceptual agents through suitable weighted sums. Various implementation strategies have been pursued with reference to: (i) the algorithm-circuit mapping (current-mode and transconductor approaches); (ii) the degree of programmability (fixed, selectable and tunable); and (iii) the implementation technology (2 and 0.8 gate lengths). Applications of the perceptual engine to machine vision algorithms are discussed.     

Parallel algorithms for image enhancement and segmentation by region growing, with an experimental study

This paper presents efficient and portable implementations of a powerful image enhancement process, the Symmetric Neighborhood Filter (SNF), and an image segmentation technique that makes use of the SNF and a variant of the conventional connected components algorithm which we call -Connected Components. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient connected components algorithm based on a novel approach for parallel merging. The algorithms have been coded in Split-C and run on a variety of platforms, including the Thinking Machines CM-5, IBM SP-1 and SP-2, Cray Research T3D, Meiko Scientific CS-2, Intel Paragon, and workstation clusters. Our experimental results are consistent with the theoretical analysis (and provide the best known execution times for segmentation, even when compared with machine-specific implementations). Our test data include difficult images from the Landsat Thematic Mapper (TM) satellite data.Also affiliated with the Department of Electrical Engineering.Also affiliated with the Department of Computer Science and the Center for Automation Research.