基于S3C2410微控制器的视频采集系统设计

视频采集及处理技术在移动设备及视频监控中有着广泛应用前景,驱动视频采集设备和获取视频数据并进行相应处理,是实现这些应用的重要的环节.针对这些实际问题和嵌入式应用技术的特点,提出了视频采集系统的设计方案.文中对基于S3C2410x(ARM9核)微控制器的硬件系统和嵌入式Linux的软件应用进行了介绍,并且阐述了视频采集与处理软件的设计过程.     

基于单片机的单总线多点温度测控系统

本课题主要介绍基于AT89C52单片机和DS18B20数字温度传感器的多点温度采集系统.该系统利用AT89C52单片机分别采集各个温度点的温度,实现温度显示、报警等功能.它以AT89C52单片机为主控制芯片,采用数字温度传感器DS18B20实现多路温度的检测,测量精度可以达到0.5℃.该系统采用了LCD1602A液晶显示模块,LCD1602A作为显示器,形象直观的显示测出的温度值.基于AT89C52单片机的单总线多点温度采集系统具有硬件组成简单、多点温度检测、读数方便、精度高、测温范围广等特点,在实际工程中得到广泛应用.     

激光图像采集存储器的设计与实现

激光图像以其高分辨率、抗干扰性强等特点得到广泛应用,但高分辨率同时表示信息量巨大,为满足激光图像的采集存储需求,设计一种针对激光图像的采集存储器。该采集存储器中,AVR单片机利用IIC总线设置激光图像采集模块工作模式,使其输出激光图像控制信号;选取FD2C13型FPGA作为控制器,通过可编程逻辑块、可编程输入输出块以及可编程互联资源块控制激光图像的传输与存储;同时通过FPGA模块中的RAM实施乒乓操作,通过调配缓存通道,提高激光图像信息吞吐量;利用压缩处理算法分块处理激光图像,基于图像矩阵像素偏差度概念和小波变换原理实现激光图像无损压缩;压缩后的激光图像通过FPGA模块控制存储在存储速度较高的MT41G07M14C3型号SRAM存储器中。实验结果表明,所设计采集存储器的采集量与存储量平均值分别为468. 4 W和408. 1 W,显著高于对比采集存储器,丢帧率降低50%以上,采集存储整体性能更优。     

基于交换拓扑的多相机拼接平台设计

在广域监控系统、侦察预警系统、仿生光学系统中广泛应用多个连接在特定光学孔径阵列上的相机进行采集拼接获得宽视场图像.随着孔径数量的增加、成像传感器分辨率的提高以及工程应用对功耗和体积的要求,多相机拼接平台的设计难度加大,图像的实时采集处理能力成为瓶颈.提出一种基于交换拓扑的多相机实时采集与处理平台架构,基于JetsonT...     

基于面阵CCD与CPLD实现的图像采集系统

介绍了一种基于面阵CCD与CPLD实现的图像采集系统，该系统能够对图像实时处理并且具有结构简单、测试精度高等特点，可作为一种便携式仪表在工程实时测量中得到广泛应用。     

基于单片机的半导体激光器应用控制技术

针对半导体激光器(LD)应用领域十分广泛的特点,提出了一种新型LD功率(P)-电流(Ⅰ)-电压(Ⅴ)的自动测试方法.该方案采用华邦51系列单片机(SCM)W78E58BP作为控制核心,实现了高稳定度的LD连续及脉冲驱动、恒流控制及功率、电压采集.LD控制单元中,应用负反馈技术实现注入电流Ⅰf、驱动电压Ⅴf和光功率Po的高稳定控制,电流控制精度为±0.1%;单片机控制电信号的放大、保持和采集,模拟、数字相结合,提高了信号处理的精度.最后,给出了通过RS-232接口对LD进行PIV测试的曲线及相关参数的测试结果,并给出了误差分析.该测试方法已得到广泛应用.     

LabVIEW与USB的直接数据通信

随着计算机技术的发展,采用LabVIEW的虚拟仪器技术得到了广泛应用;使用LabVIEW对信号进行分析和处理依赖于数据的采集,数据采集通常的方法是使用数据采集卡,但如PXI,PCI等数据采集卡价格较贵,使用也不方便,影响了LabVIEW的推广和使用。USB总线具有使用方便、接口简单、传送速率高的特点,使用USB接口进行数据的采集不失为一种可供选择的方案。介绍了一种LabVIEW和USB设备进行直接数据通信的实用方法。     

电力自动化系统中电量采集和计量的运用

本文主要通过对电力自动化系统的介绍,详细的分析了电力自动化系统中电量采集和计量的运用,并且在此基础上在,探讨了提高电力自动化系统中的电量采集和计量准确性的对策,希望能够为我国电力自动化系统的广泛应用提供借鉴,能够为电力采集与计量工作水平的提高提供借鉴.     

基于堆栈自编码器的脉搏信号远程监测技术研究

传统的脉搏信号监控能够准确地反映出病人心血管系统的病理变化,但由于分析处理过程繁琐,导致难以广泛应用.为了解决远程医疗的信号采集难、数据可信度难以保证的问题,文中研究了脉搏信号的远程监控技术.采用Arduino Nano微控制器,基于电路集成技术设计了嵌入式随身生物信号采集器,解决了脉搏信号采集困难的问题,实现了对脉搏...     

车辆自动识别系统移动站及其在城市交通监管中的应用

车辆自动识别系统 (AVI)移动站具有机动、快速和自动识别车辆的特点 ,适合于在城市监管中广泛应用。它采用射频识别 (RFID)技术 ,通过车卡 (TAG)采集车辆数据信息 ,对车辆进行自动识别和处理 ,识别率超过 99%;采用视频识别 (VFID)技术 ,通过摄像机采集车辆图像信息 ,在光照较强的情况下 ,识别率可以达到 80 %以上。     

基于USB 2.0的同步数据采集系统的设计

针对当前工程中数据采集要更快更精确的要求,提出了一种新的数据信号采集系统。他采用的方法是利用USB 2.0接口芯片CY7C68013A和AD7658来实现同步多路数据采集以及与计算机间的通信。实验结果说明,该系统数据传输效率高、工作稳定,很好地满足设计要求。这种设计方法不但切实可行,且具有同步、高速、电路简单等特点,可以满足多种工程设计的要求,是一种很值得推广的数据采集方法。     

基于属性相关性划分的多敏感属性隐私保护方法

近年来,基于l-多样性的多维敏感属性的隐私保护研究日趋增多,然而大部分多敏感属性隐私保护方法都是基于有损分解的思想,破坏了数据间的关系,降低了数据效用.为此,提出了一种面向多敏感属性的隐私模型,首先给出一种l-maximum原则用以满足多敏感属性l-多样性要求;其次,为了保护属性间的相关性,根据属性间的依赖度对属性进行划分;最后设计并实现了MSA l-maximum（Multiple Sensitive Attributes l-maximum）算法.实验结果表明,提出的模型在保护隐私不泄露的同时,减少了元组的隐匿率,并且保护了数据间的关系.     

TDAT-time domain analysis tool for EEG analysis

An interactive design and analysis tool for displaying and quantifying multiple channels of data is presented. The system allows one to easily visualize multiple data channels and simultaneously observe the effects of filters on the data and to evaluate signal detection algorithms. The software is designed for a workstation environment; it will find application in a variety of applications where one needs to simultaneously visualize multiple data channels. TDAT is being used for the design and evaluation of filters and detection algorithms for electroencephalogram (EEG) waveforms, and it is serving as a prototype of a paperless system to be used by electroencephalographers. This paper describes the general software structure of the system and illustrates many of the system features with examples.     

A Spatial Correlation Based Adaptive Missing Data Estimation Algorithm in Wireless Sensor Networks

In wireless sensor networks, the missing of sensor data is inevitable due to the inherent characteristic of wireless sensor networks, and it causes many difficulties in various applications. To solve the problem, the missing data should be estimated as accurately as possible. In this paper, an adaptive missing data estimation algorithm is proposed based on the spatial correlation of sensor data. It adopts multiple regression model to estimate the missing data with the data of multiple neighbor nodes jointly rather than independently, which makes its estimation performance stable and reliable. In addition, for different missing data, it can adjust the estimation equation adaptively to capture the dynamic correlation of sensor data. Thereby, it can estimate the missing data more accurately. Further more, it can also give the confidence interval of each missing data for the given confidence level, which is helpful greatly for users. Experimental results on two real-world datasets show that the proposed algorithm can estimate the missing data accurately.     

基于纠删码的分布式存储系统中针对多数据失效的树型并行修复技术

To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge- sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are dis-tributed over a large area and have few inter-sections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available bandwidth and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two op-timizations: firstly, transferring the data thr-ough the bandwidth optimized-paths in a pipeline manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event- based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.     

基于旋转干涉仪圆阵化的多目标参数估计新算法

针对现有的长基线旋转干涉仪存在相位模糊,且不能对多个同频、同时到达的目标信号进行角度估计问题,该文提出一种基于旋转干涉仪虚拟圆阵化的多目标波达参数估计新算法。该方法首先将旋转干涉仪采样得到的两通道数据进行共轭相乘操作,获得虚拟圆阵信号;然后采用波束空间变换法将虚拟圆阵数据从阵元空间转换到波束空间,得到虚拟线阵数据序列;最后在实波束域上实现多目标2维角度无模糊估计。相比于传统旋转干涉仪方法而言,所提方法在不增加接收通道的同时,能够实现多目标角度的无模糊测量。仿真实验验证了所提方法的有效性。     

靶场中多飞行目标的航迹保持�

多飞行目标的跟踪应用广泛,在靶场中需要对多飞行目标进行跟踪监测时,要排除目标所受的各种干扰因素,当多飞行目标之间出现相互运动时,为保证判断目标击中的准确性,需要对多飞行目标航迹达到稳定保持的测量。因此,系统以靶场中多飞行目标为跟踪对象,着重研究多飞行目标序号保持不变问题。通过不同检测方法对目标的特征提取效果进行对比,并且将多参数的数据关联算法应用于系统的多目标跟踪中,验证得出,在背景均方差MSE介于4.0~5.0之间的情况下,当目标数量多达12个时,其目标序号保持的准确度比PDA算法提高23.29%。     

Superposition Coding and Analysis for Cooperative Multiple Access Relay System

The conventional straightforward relaying scheme named decode-and-forward (DF) protocol is used at relay to decode the data received from source and forward the decoded data to the destination to improve the spatial diversity gain. Although it is a simple scheme, the total resource efficiency is low for multiple sources. Superposition coding has been known as a spectral efficient technique in wireless networks. However, when it is applied to the uplink multiple access relay systems, it suffers from performance degradation caused by the power allocation between the symbols of multiple sources. In this paper, we propose to remedy this problem by using hierarchical modulation at the source node and superposition coding at the relay node to enhance the bit energy. We investigate how hierarchical modulation can be incorporated and optimized with superposition coding. Specially, we discuss the capacity behavior of the proposed scheme and compare with the baseline, namely the capacity behavior of the existing DF scheme and the capacity behavior of the superposition coding. Our results are encouraging in that superposed hierarchical modulation significantly improves the better block error rate and capacity performance in multiple access relay channels.     

Multimedia annotation via semi-supervised shared-subspace feature selection

With the rapid development of social network and computer technologies, we always confront with high-dimensional multimedia data. It is time-consuming and unrealistic to organize such a large amount of data. Most existing methods are not appropriate for large-scale data due to their dependence of Laplacian matrix on training data. Normally, a given multimedia sample is usually associated with multiple labels, which are inherently correlated to each other. Although traditional methods could solve this problem by translating it into several single-label problems, they ignore the correlation among different labels. In this paper, we propose a novel semi-supervised feature selection method and apply it to the multimedia annotation. Both labeled and unlabeled samples are sufficiently utilized without the need of graph construction, and the shared information between multiple labels is simultaneously uncovered. We apply the proposed algorithm to both web page and image annotation. Experimental results demonstrate the effectiveness of our method.     

基于嵌入式LINUX的异步事件驱动数据采集模型

提出了一种基于嵌入式Linux的高性能多路数据采集软件模型．该模型采用ACE设计模式提供的体系架构，实现了异步事件驱动的并发处理，能支持事件多路分离，异步操作结束会触发事件句柄，再调用回调函数完成相应的数据处理任务。由于对数据源事件的监测、数据读取、多事件的处理等操作是由操作系统完成．该模型可以有效避免多进程同步机制系统开销较大的问题，从而提高嵌入式系统的多路数据并发采集能力。