超高频射频识别读写器的研究与设计

超高频射频识别系统具有存储容量大、读写速度快、识别距离远和可同时读写多个电子标签等特点,已经在众多领域得到了广泛的应用。为了满足市场需求,对超高频读写器的内部结构进行了研究并提出了一种基于ARM的超高频射频识别系统读写器的设计方案。从硬件和软件两个方面对读写器的设计进行了阐述,给出了读写器的设计结构、工作流程以及相关的软件流程图。实际应用结果表明,该读写器具有读写速度快、读写效率高、识别距离远等优点,可以满足市场需求。     

通过人脸识别技术限制重复投票的电子投票系统的设计

将人脸识别技术应用于电子投票系统中,限制重复投票行为.首先分析了该电子投票系统的结构,给出了人脸识别技术在限制重复投票行为中的应用场景.针对电子投票系统对人脸识别算法的需求以及投票人图像采集背景简单和光照变化较小的特点,分析了适用于本系统的基于AdaBoost的人脸检测方法以及基于特征脸的人脸识别方法,给出了通过OpenCV实现的基于人脸识别方法的身份认证子系统的设计流程,并介绍了基本投票子系统各模块的功能.最后对身份认证子系统的性能进行了分析.     

Efficient Embedded Neural-Network-Based License Plate Recognition System

In this paper, a video processing methodology for a field-programmable gate array (FPGA)-based license plate recognition (LPR) system is researched. The raster scan video is used as an input with low memory utilization. During the design, Gabor filter, threshold, and connected component labeling (CCL) algorithms are used to obtain license plate region. This region is segmented into disjoint characters for the character recognition phase, where the self-organizing map (SOM) neural network is used to identify the characters. The system is portable and relatively faster than computer-based recognition systems. The robustness of the system has been tested with a large database acquired from parking lots and a highway. The memory requirements are uniquely designed to be extremely low, which enables usage of smaller FPGAs. The resulting hardware is suitable for applications where cost, compactness, and efficiency are system design constraints.      

超高频射频识别读写器的研究与设计

超高频射频识别系统具有存储容量大、读写速度快、识别距离远和可同时读写多个电子标签等特点,已经在众多领域得到了广泛的应用。为了满足市场需求,文章对超高频读写器的内部结构进行了研究,并提出了一种基于ARM的超高频射频识别系统读写器的设计方案。文中从硬件和软件两个方面对读写器的设计进行了阐述,给出了读写器的设计结构、工作流程...     

视频检测算法研究与FPGA实现

视频检测、跟踪、识别一直是智能监控、视频检索、模式识别相关领域研究的热点。在此使用FPGA作为系统的控制模块,实现了基于背景寄存检测算法的检测系统。该系统在满足实时性要求的同时,较好地完成了检测任务。并用在QuartusⅡ,ModelSim进行混合仿真,避免了硬件平台的限制,增加了实现的成功率。     

基于整数小波的图像处理系统在硬件中的实现

随着互联网的普及和图像应用范围的不断扩大, 对图像的处理提出了新的要求,即不仅要求对图像识别的准确,还要求达到实时处理,因此系统以高性能数字信号处理器ADSP-BF561和大规模现场可编程门阵列(FPGA)作为核心,结合离散整数小波变换,在硬件系统上实现提升方法的整数小波变换和Mallat算法小波变换,取得了较好的试验效果.     

基于nRF2401的牲畜信息读写器的研究

应用在动物识别领域中的RFID读写器是畜产品溯源系统的信息输入起点,它的性能直接影响了畜产品溯源系统的质量。为了开发出一种能适应具体应用环境的读写器,在充分理解动物识别领域对读写器的特殊需求后,确定了系统的设计方案,并选择了适当的器件,采用模块化的设计思想,开发出一种能够在远距离、动物快速运动的状态下能可靠读/写信息的读写器。     

基于KPCA和LSSVM的表面缺陷深度识别

为了实现铝板表面缺陷智能识别分类,解决支持向量机在识别过程中准确率不高的问题,对核主成分分析(Kernel Principal Component Analysis,KPCA)和最小二乘支持向量机(Least Square Support Vector Machine,LSSVM)在缺陷深度识别分类的应用进行了研究。采用核主成分分析算法对实验获取的激光超声信号进行时域特征参数提取主成分,并将多个满足要求的主成分作为输入,建立KPCA-LSSVM分类模型对表面缺陷进行识别。结果表明,该模型精准率和召回率高于优化前的系统,识别准确率达到了95%。     

光纤传感与红外视频的复合入侵监控系统设计

针对机场、油库等特定区域的高识别率、低误报率入侵事件监控需求,提出了一种基于光纤传感与红外视频的目标识别方法。其中,光纤传感部分采用基于MCSVM的非对称双马赫-曾德尔干涉仪（ADMZI）分布式光纤振动传感器,将EMD(经验模式分解)、将峰度特征与MCSVM相结合以提高识别率;红外识别部分将灰度差值图像通过小波变换提高清晰度。两者经过模式对比算法,实现入侵事件判定。搭建系统做现场实验,结果表明:该方法能够识别四种常见的入侵事件(爬越围栏、敲击电缆、剪断围栏、摇动围栏),平均识别率在92.5%以上,误报率0.9%,相对传统单一传感器方案,该方法在漏报率和虚警率等系统性能上都有较大的改善,能够满足实际应用要求。     

嵌入式数字语音拨号系统的研究与实现

将语音识别技术应用于拨号系统,在嵌入式平台上实现了一款针对非特定人的数字语音拨号系统。语音识别算法中选择梅尔频率倒谱系数为特征参数,连续隐马尔科夫模型。为训练和识别过程模型,利用Qt界面对识别过程进行控制,系统针对非特定人数字语音识别进行实验。结果表明,系统针对非特定人识别率达到了98％,识别时间为3．55S。识别率和实时性都满足语音拨号的需求。     

Neural networks for statistical recognition of continuous speech

In recent years there has been a significant body of work, both theoretical and experimental, that has established the viability of artificial neural networks (ANN's) as a useful technology for speech recognition. It has been shown that neural networks can be used to augment speech recognizers whose underlying structure is essentially that of hidden Markov models (HMM's). In particular, we have demonstrated that fairly simple layered structures, which we lately have termed big dumb neural networks (BDNN's), can be discriminatively trained to estimate emission probabilities for an HMM. Recently simple speech recognition systems (using context-independent phone models) based on this approach have been proved on controlled tests, to be both effective in terms of accuracy (i.e., comparable or better than equivalent state-of-the-art systems) and efficient in terms of CPU and memory run-time requirements. Research is continuing on extending these results to somewhat more complex systems. In this paper, we first give a brief overview of automatic speech recognition (ASR) and statistical pattern recognition in general. We also include a very brief review of HMM's, and then describe the use of ANN's as statistical estimators. We then review the basic principles of our hybrid HMM/ANN approach and describe some experiments. We discuss some current research topics, including new theoretical developments in training ANN's to maximize the posterior probabilities of the correct models for speech utterances. We also discuss some issues of system resources required for training and recognition. Finally, we conclude with some perspectives about fundamental limitations in the current technology and some speculations about where we can go from here     

Automated conversion of engineering drawings to CAD form

The authors present a discussion of the different aspects and requirements of the CAD conversion problem and describe the general architecture and algorithms of one commercially available CAD conversion system, the GTX 5000. Scanning, vectorization, text recognition, symbol recognition, context processing, and cleanup editing subsystems of the GTX 5000 are described. Several possible alternative approaches and algorithms are also compared. EPRI (Electric Power Research Institute)-funded enhancements are discussed, including neural networks for character and symbol recognition, touching and broken character processing, and text/symbol associativity     

基于最大似然译码的快速信道编码盲识别算法

本文针对信道编码盲识别的盲译码过程延时高的问题,提出一种基于最大似然译码的信道编码盲识别算法。该识别算法通过以最大似然译码的欧氏距离值作为识别特征量的方式,将信道译码和信道编码识别相结合。这种算法可以在信道译码过程中提前识别并终止无效译码以达到加速目的。本文利用NP准则推导出满足系统可靠性需求的最佳检测阈值。该识别算法原理简单,实现容易。仿真结果证明了理论推导的正确性,表明所提出算法在信道编码识别中具有良好的识别性能。      

基于LPCC参数的语音识别系统

为了识别简单语音,设计了一个基于LPCC参数的语音识别系统。该系统其主要功能有语音信号的录制、播放、预处理、分段滤波、特征提取以及识别语音。最后通过仿真实验验证了本系统能够达到识别简单语音的要求,但仍有需改进的地方,如:能否在复杂环境下识别比较复杂的语音。     

A modularized processor LSI with a highly parallel structure forcontinuous speech recognition

A speech recognition processor CMOS LSI was developed as the processing element (PE) of a ring array processor previously proposed by the authors as architecture to carry out highly parallel recognition processing with array size flexibility. There are three key features for the LSI: (1) a highly parallel I/O structure of triple buffer with cyclical-mode transition control methods to solve the serious problem of inter-PE data transfer overhead versus the array processing; (2) a control structure with two direct memory access (DMA) controllers to realize inter-PE data I/O processing and intra-PE processing in parallel; and (3) a pipelined recognition processing at a high execution rate realized by a pipelined structure and a balanced clock distribution design technique. These effective designs for the PE LSI allow high-speed recognition processing without any inter-PE data transfer overhead in the ring array processor. Combining the PE-LSI architecture with the proposed array architecture for highly parallel dynamic time warping (DTW) processing, a real-time continuous speech recognition system based on continuous dynamic programming matching using the SPLIT method for a 1000-word vocabulary, can be constructed using a ring array processor consisting of 30 PEs     

机载毫米波脉冲多普勒雷达旋翼目标识别技术研究

旋翼目标是机载毫米波脉冲多普勒雷达低空与地面目标中的首要识别对象,由于其回波频谱展宽与波长成近似反比关系,使其在毫米波段呈现低信杂比、弱特征现象。本文首先在分析毫米波雷达旋翼目标特性的基础上,针对旋翼识别难题,对雷达系统前端的波束驻留时间、脉冲重复周期、杂波抑制性能、相参积累脉冲数、频综器相位噪声谱密度等参数设计提出了新的要求;之后,设计了专用目标识别软件平台,并给出了面向工程应用的专用目标识别软件总体结构,提出了利用噪声归一化的频谱数据预处理技术、识别结果积累策略以及多普勒频谱层析图分析等信号处理方法;最后,利用实测数据提取特定的特征对目标进行识别分类,并对部分中间结果进行了详细分析,实验结果验证了本文方法的有效性,对旋翼和固定翼目标具有良好的分类识别性能。      

电子装备生产调测线网络化测试技术研究

针对离散型制造车间电子装备生产调测线中存在的多品种批量测试压力大的问题,结合制造物联技术的应用重新定义当前测试过程,设计具有实时测试信息特征的工作模式和通信手段,以适应车间数字化改造升级的要求。以离散车间自动测试系统为研究对象,通过搭建面向实时测试过程的工业物联识别环境,构建自动测试系统信息化体系框架,详细分析了基于开关切换和自动化流水线的多被测件测试技术、现场设备在线互操作协同技术、基于实时跟踪的数据通信技术等关键技术,给出了基于浏览器/服务器结构的网络化柔性测试生产线实现方法,为提升制造车间的整体测试服务水平提供了基础。     

空基预警探测系统技术发展趋势

空基预警探测系统是空基信息系统的重要组成部分。文中分别分析了空基信息系统面临的隐身目标探测、目标综合识别和复杂战场对抗三个需求,从而提出了未来空基预警探测系统技术的发展趋势。     

嵌入式人体步态自动识别系统

提出了基于双目立体视觉进行步态识别,并且利用数据融合方法对由光流场中提取出的步态特征进行数据融合,然后对融合后的有效特征进行步态识别,并给出了评估步态识别的有效性与错误率。利用Renesas 32位嵌入式系统在总体结构上对步态自动识别系统进行了设计,以符合大多数场合的需要。     

针对持续入侵事件的分级识别算法

提出了一种基于应激反应过程的光纤预警分级 识别算法。该 算法受启发于人体受到外界刺激时机体分阶段调用组织系统和能量进行抵抗的机制,针对持 续振动的光纤 信号设计了分级识别算法。对于持续入侵事件引起的光纤振动信号,首先用高识别精度、高 时间消耗的算 法进行短时间的识别,以确定当前入侵事件类型;后续振动信号用低识别率、低时间消耗的 算法进行识别, 以监测是否新入侵事件产生。当发现新入侵事件后,需用高识别率的算法再次识别以查正。 实验结果表明,本算法能在一定识别精度下识别速度提升为原来的3.67倍,保证了保证了系统实时性监测的要求。