双通道矢量信号分析仪测试系统延迟特性

测试目的使用双通道分析仪测试两路相位相参的调制信号间的时间关系,验证该方案在两项应用中的可行性。一方面验证使用相关技术方法测试信号间时间关系的可行性,另一方面通过对被测电路的输出和输入信号的相关测试,得到电路在复杂激励状态下的延迟特性。通过测试,检验Agilent双     

测试系统延迟特性双通道矢量信号分析仪显身手

双通道分析仪表可用来测试两路相位相参的调制信号间的时间关系,并验证该方案在两项应用中的可行性.一方面验证使用互相关技术方法测试信号间时间关系的可行性,另一方面通过对被测电路器件的输出和输入信号的相关测试,得到电路在复杂激励状态下的延迟特性.通过实验测试,检验双通道矢量信号分析仪分析测试双路调制信号时间关系的功能和性能.     

用于测试混合信号测试的任意波形发生器

AWG5000系列任意波形发生器基于与AWG7000系列相同的平台。客户可以使用一台AWG5000，生成高分辨率信号，在测试混合信号设备中模拟电路和数字基带电路和中间频率（IF）电路，提高测试效率，降低测试成本。     

一种混合信号测试系统的设计及实现

针对一款混合信号的视频编解码芯片的参数测试要求,依据电路内部的测试结构,设计了一个基于纯数字自动测试设备（ATE）的混合信号电路测试系统。该测试系统通过增加MCU、ADC、DAC、FIFO、运放、可控开关等外围电路实现对芯片参数的测试。详细阐述了测试系统的总体方案、硬件设计和软件设计。通过软件和硬件的协同工作,该测试系统能够对含有AD、DA模块的混合信号电路相关参数进行测试,实现电路整体性能的评估。该测试系统原理清晰,结构简单,扩展灵活、方便。     

介绍一种测试方法:多路,连续信号的计算机实时处理

用计算机对多通道信号进行测试，其关键问题之一是将连续的信号离散化。本文就某测试调试设备中，如何对４４路通道的信号同时进行电路在线测试，给出了连续信号离散化的方法，以及编程前的数据组织结构。     

浅析模拟与混合信号电路测试与故障检测方法

模拟和混合信号电路本身具有相当高的复杂性及专业性,使得模拟和混合信号电路测试与故障检测无法在传统数字电路测试方法下得到满足。文章通过介绍模拟和混合信号电路测试与故障检测的研究现状,分析了模拟与混合信号电路的测试与故障检测方法,并在传统测试技术的基础上研究了新的诊断方法,具有参考价值。     

使用NI PXI-5660射频信号分析模块开发手机在线测试系统

挑战：使用现成即用的商业产品减少手机测试成本．缩短测试时间．完成无线协设参数测试解决方案：使用NI PXI-566,0射颤信号分析模块和全新开发的LabVlEW无线测试工具包．建立一套基于PXI的自动化手机参数测试系统．来取代价格昂贵．灵活性差的传统台式仪器     

基于Verigy 93000的GMH 92 LV 18全参数测试技术

以GMH 92 LV 18为研究对象,研究了其功能与全参数测试方法,重点研究并形成了与该器件相关的功能测试方法、异步信号处理技术、信号的稳定生成技术、程控动态负载测试技术和时间参数测试技术,并给出了在Verigy 93000测试系统上的实测波形图。对Verigy 93000测试系统上的器件测试、LVDS器件测试及高速信号测试均具有借鉴意义。     

一种高精度测频电路设计

一种高精度测频电路设计朱大奇（华东冶金学院，２４３００２）１．引言信号频率测试的方法很多，常用的有直接测频的门控时间计数法和测周期的间接测频法等。这两种方法原理基本相同，易于实现，但测频精度不是很高，下面介绍的一种测频电路是在直接测频法基础上进行改进...     

高灵敏加速度计微弱信号提取电路设计与测试

介绍了一种压阻式高灵敏加速度传感器微弱信号提取电路。该信号提取电路采用两级信号放大设计,两级之间设计有二阶巴特沃兹低通滤波器。本设计电路通过电路仿真软件进行仿真和外接加速度计测试。测试结果表明,该微弱信号检测提取电路可以很好地对高灵敏MEMS加速度计输出的信号进行放大,具体表现为可将传感器输出信号从毫伏级放大到伏级。采用这种电路设计的MEMS高灵敏加速度计输出信号具有良好的低频特性,可以满足高灵敏传感器宽频带测试的需要。     

飞机遇险呼救还是干扰信号?

121．5MHz是国际电联规定的飞机遇险呼救专用频率，其他任何部门和个人不得占用。一旦出现呼救信号，必须立即找到信号源．否则后果不堪设想。     

Le traitement du signal vocal voice signal processing

The speech processing studies have advanced rapidly in recent years spurred on by great progresses in thevlsi technologies and in the digitalization of the networks. This paper offers an overview of the most attractive techniques which have focused the recent researchs and developments in speech coding, recognition and synthesis areas. For speech compression, the emphasis is put on a family of techniques named code-excited linear prediction (celp) which dominates current studies for rates in the range of 4 to 16 kbit/s. In terms of speech recognition, particular emphasis is placed on the following three elements which are essential in order to increase the robustness of the systems : telephone line adaptation, rejection of parasite noise and out-of-vocabulary words, and keyword spotting. In terms of text-to-speech synthesis, thepsola (pitch synchronous overlap and add) technique is outlined herein. This technique gives rise to a new generation of synthesis systems which produce speech with very natural timbre. The analysis of current tendencies for each area allows to suggest attractive directions for future research.     

基于矢量信号发生器的微波着陆信号模拟

针对当前微波着陆装备测试的迫切需要,提出一种基于矢量信号发生器硬件架构的微波着陆模拟器的实现方式,并提出了一种基于FPGA的微波着陆系统基带信号设计方法。对微波着陆信号的格式和信号时序进行了仿真,并对各种角功能信号和数据字结构进行了实际测试,证明了该模拟器性能达到装备测试要求。     

集成语音信号与表面肌电信号的情感自动识别模型

为了提高情感识别的正确率,针对单一语音信号特征和表面肌电信号特征存在的局限性,提出了一种集成语音信号特征和表面肌电信号特征的情感自动识别模型.首先对语音信号和表面肌电信号进行预处理,并分别提取相关的语音信号和表面肌电信号特征,然后采用支持向量机对语音信号和表面肌电信号特征进行学习,分别建立相应的情感分类器,得到相应的识别结果,最后将识别结果分别输入到支持向量机确定两种特征的权重系数,从而得到最终的情感识别结果.两个标准语情感数据库的仿真结果表明,相对于其它情感识别模型,本文模型大幅提高了情感识别的正确率,人机交互情感识别系统提供了一种新的研究工具.     

Multiple digital signal processor environment for intelligent signal processing

We describe a novel, expandable, multiple digital signal processor (DSP) architecture with a symbolic processing host. A multiprocessor board, called Odyssey, based on this architecture has been developed to combine symbolic and real-time digital signal processing in a single computing environment. Some of the key features of the board are: 20 million multiply/accumulates per second, 512K bytes of data space, and expandability to 16 boards on a NuBus host. The DSPs used are the TMS32020 signal processing chips developed by Texas Instruments, and the host is Texas Instruments' Explorer, a LISP machine workstation. This provides environment to perform many intelligent signal processing tasks by associating meaningful relationships between quantitative (signal processing) and qualitative (symbolic processing) entities to develop inferences using expert system technology. Applications such as grammar-driven connected speech recognition, neural network simulation, EEG analysis, and generation of speech from general English text with natural language processing are some of the tasks that can utilize the computational power of the multiple DSP and/or the associated symbolic processing capabilities. Software development tools to implement applications include the device driver to facilitate communication between the host processor and the Odyssey board, a unique window-based debugger resident on the Explorer that allows for simultaneous state display of all the processors on the board, a FORTH interpreter for high-level language programming, and a cross-assembler/linker for assembly level programming.     

Adaptive machine learning algorithm employed statistical signal processing for classification of ECG signal and myoelectric signal

Multidimensional Systems and Signal Processing - In this research paper we present designing and evaluating the electrocardiography (ECG) and Myoelectric signal (EMG) pattern recognition methods...     

Resonance-based signal decomposition: A new sparsity-enabled signal analysis method

Numerous signals arising from physiological and physical processes, in addition to being non-stationary, are moreover a mixture of sustained oscillations and non-oscillatory transients that are difficult to disentangle by linear methods. Examples of such signals include speech, biomedical, and geophysical signals. Therefore, this paper describes a new nonlinear signal analysis method based on signal resonance, rather than on frequency or scale, as provided by the Fourier and wavelet transforms. This method expresses a signal as the sum of a ‘high-resonance’ and a ‘low-resonance’ component—a high-resonance component being a signal consisting of multiple simultaneous sustained oscillations; a low-resonance component being a signal consisting of non-oscillatory transients of unspecified shape and duration. The resonance-based signal decomposition algorithm presented in this paper utilizes sparse signal representations, morphological component analysis, and constant-Q (wavelet) transforms with adjustable Q-factor.     

基于信号子空间的直接序列扩频信号波形估计方法

将直接序列扩频(DS-SS)信号波形估计问题归结为信号子空间估计问题,提出基于传播算子算法的扩频波形估计方法。针对特征值分解求解信号子空间计算量较大的问题,利用传播算子估计信号子空间,并对算法计算量和性能进行理论分析和实验验证,结果表明该算法有效,且计算量远小于现有算法。     

数字信号处理及DSP芯片的发展前景

简要介绍了DSP的设计流程及其实现方法,着重介绍了DSPs芯片结构特点、运算速度、应用与市场,并展望了DSPs芯片的发展前景。