Frequency Specification Testing of Analog Filters Using Wavelet Transform of Dynamic Supply Current

Wavelet transform has the property of resolving signal in both time and frequency unlike Fourier transform. In this work, we show that time-domain information obtained from wavelet analysis of supply current can be used to test the frequency specification of analog filters efficiently. The pole/zero locations in the frequency response of analog filters shift due to change in component values with process variations. It is essential to test the filters for the shift in frequency response and fix it during production test. Wavelet analysis of supply current can be a promising alternative to test frequency specification of analog filters, since it needs only one AC stimulus and is virtually unaffected by transistor threshold variation. Simulation results on two test circuits demonstrate that we can estimate pole/zero shift with less than 3% error using only one measurement, which requires about 18 measurements in the conventional technique.Swarup Bhunia received the undergraduate degree from Jadavpur University, Calcutta, India, and the Masters degree from the Indian Institute of Technology (IIT), Kharagpur. He is currently working toward the Ph.D. degree in the Department of Electrical Engineering, Purdue University, West Lafayette, IN, USA. He has worked in the EDA industry on RTL synthesis and verification for about three years. His research interest includes design methodologies for high-performance low-power testable VLSI system, defect-based testing, noise analysis, and noise-aware design.Arijit Raychowdhury received the B.E. degree in 2001 in electronics and telecommunication engineering from Jadavpur University, India. He is currently pursuing the Ph.D. degree in electrical and computer engineering in Purdue University, West Lafayette, IN, USA. He has worked as an analog circuit designer in Texas Instruments India. His research interests include device/circuit design for scaled silicon and nonsilicon devices. He has received academic excellence awards in 1997, 2000, and 2001 and Messner Fellowship from Purdue University in 2002. Mr. Raychowdhury has been awarded the Best Student Paper Award in the IEEE Nanotechnology Conference, 2003.Kaushik Roy received the B.Tech. degree in electronics and electrical communications engineering from the Indian Institute of Technology, Kharagpur, India, and the Ph.D. degree from the Electrical and Computer Engineering Department, University of Illinois, Urbana, in 1990. He was with the Semiconductor Process and Design Center of Texas Instruments, Dallas, TX, where he worked on FPGA architecture development and low-power circuit design. He joined the electrical and computer engineering faculty, Purdue University, West Lafayette, IN, in 1993, where he is currently a Professor. His research interests include VLSI design/CAD with particular emphasis in low-power electronics for portable computing and wireless communications, VLSI testing and verification, and reconfigurable computing. He has published more than 250 papers in refereed journals and conferences, holds six patents, and is Co-Author of a book on Low Power CMOS VLSI Design (New York: Wiley). He was Guest Editor for a Special Issue on Low-Power VLSI in IEE Proceedings Computers and Digital Techniques (July 2002). Dr. Roy received the National Science Foundation Career Development Award in 1995, the IBM Faculty Partnership Award, AT&T/Lucent Foundation Award, Best Paper Awards at the 1997 International Test Conference and 2000 International Symposium on Quality of IC Design, 2003 IEEE Latin American Test Workshop, and 2003 IEEE Nano. He is on the Editorial Board of IEEE Design and Test, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS, and IEEE TRANSACTIONS ON VLSI SYSTEMS. He was Guest Editor for a Special Issue on Low-Power VLSI in IEEE DESIGN AND TEST (1994), and for the IEEE TRANSACTIONS ON VLSI SYSTEMS (June 2000).     

基于小波高频系数统计特征的电路故障诊断

对故障电路进行特征提取与分类是模拟电路诊断的两个重要环节。现有方法多对时域响应信号进行小波变换以提取故障特征,并用神经网络或支持向量机方法实现对故障进行分类。为提高模拟电路故障诊断率,提出一种新的特征选取方法:在模拟电路的时域响应中对其进行小波变换,并对变换得到的高频细节系数统计平均值、标准偏差、峭度、熵和偏斜度等统计特征,并建立以支持向量机为分类器的故障诊断系统。以两种常见电路为例,实验结果表明,提出方法对常见电路进行故障诊断,准确率得到提升,精度达到99%以上,优于传统单纯小波系数分析方法,适用于模拟电路的故障诊断。     

Fault Diagnosis of Nonlinear Analog Circuits Using Neural Networks with Wavelet and Fourier Transforms as Preprocessors

A neural-network based analog fault diagnostic system is developed for nonlinear circuits. This system uses wavelet and Fourier transforms, normalization and principal component analysis as preprocessors to extract an optimal number of features from the circuit node voltages. These features are then used to train a neural network to diagnose soft and hard faulty components in nonlinear circuits. Our neural network architecture has as many outputs as there are fault classes where these outputs estimate the probabilities that input features belong to different fault classes. Application of this system to two sample circuits using SPICE simulations shows its capability to correctly classify soft and hard faulty components in 95% of the test data. The accuracy of our proposed system on test data to diagnose a circuit as faulty or fault-free, without identifying the fault classes, is 99%. Because of poor diagnostic accuracy of backpropagation neural networks reported in the literature (Yu et al., Electron. Lett., Vol. 30, 1994), it has been suggested that such an architecture is not suitable for analog fault diagnosis (Yang et al., IEEE Trans. on CAD, Vol. 19, 2000). The results of the work presented here clearly do not support this claim and indicate this architecture can provide a robust fault diagnostic system.     

一种动态电流测试产生方法的SPICE模拟验证

数字电路状态发生改变时,数字电路中的逻辑跳变直接影响电路中的动态电流.基于布尔过程的波形模拟器能够快速准确地对电路进行模拟,其结果既能反映电路的逻辑特性又能反映电路的定时特性.利用波形模拟器可以准确的了解电路中跳变的情况.本文利用波形模拟器改进并实现了一种基于逻辑跳变计数的动态电流测试方法.对于S208电路中的部分开路故障和延时故障,本文用该方法产生了一组测试结果,并利用SPICE软件对这些测试结果进行了模拟实验.模拟结果表明,对于某些故障,测试向量对能够使故障电路的动态电流和无故障电路的动态电流产生较大的差别.通过比较两者平均动态电流的大小,我们能够区分出故障电路和无故障电路.实验结果验证了本文中的动态电流测试产生方法的有效性和可行性.     

Dynamic Power Supply Current Testing of CMOS SRAMs

We describe the design and implementation of a dynamic power supply current sensor which is used to detect SRAM faults such as disturb faults as well as logic cell faults. A formal study is presented to assess the parameters that influence the sensor design. The sensor detects faults by detecting abnormal levels of the power supply current. The sensor is embedded in the SRAM and offers on-chip detectability of faults. The sensor detects abnormal dynamic current levels that result from circuit defects. If two or more memory cells erroneously switch as a result of a write or read operation, the level of the dynamic power supply current is elevated. The sensor can detect this elevated value of the dynamic current. The dynamic power supply current sensor can supplement the observability associated with any test algorithm by using the sensor as a substitute for the read operations. This significantly reduces the test length and the additional observability enhances defect coverages.     

基于开关电流技术的连续小波变换的实现方法

开关电流技术是一种新的模拟抽样数据处理技术。开关电流电路具有一般电路不具有的优点，与标准数字CMOS工艺兼容。连续小波变换是分析非平稳信号的有力工具，在信号处理上有广泛的应用。本文提出用开关电流技术实现连续小波变换的方法，并用Matlab仿真证明了其理论可行性。     

Classification of Defective Analog Integrated Circuits Using Artificial Neural Networks

This paper presents a new approach for detecting defects in analog integrated circuits using the feed-forward neural network trained by the resilient error back-propagation method. A feed-forward neural network has been used for detecting catastrophic faults randomly injected in a simple analog CMOS circuit by classification the differences observed in supply current responses of good and faulty circuit. The experimental classification was performed for time and frequency domain, followed by a comparison of results achieved in both domains. It was shown that neural networks might be very efficient and versatile approach for test of analog circuits since an arbitrary fault class or circuit's parameter can be analyzed. Considered defect types and their successful detection by the neural network; and a possible off-chip hardware implementation of the proposed technique are discussed as well. Moreover, optimized hardware architecture of the selected neural network type was designed using VHDL for FPGA realization.     

Control and Observation Structure for Analog Circuits with Current Test Data

This work presents a current-mode control and observation structure (CMCOS) for analog circuits with current test data. Current store cells (CSCs) are used in the proposed CMCOS to enhance the controllability and observability. The proposed CMCOS can be used to observe several test points, which can be simultaneously sampled and controlled using current test data. Additionally, the proposed CMCOS enables designers to use one channel of an oscilloscope to monitor simultaneously several output waveforms of analog circuits or systems. The physical chip of a two-stage CMCOS was fabricated using TSMC 1P4M CMOS 0.35 um technology. Also, experiments were performed to confirm the theoretical analysis.     

小波变换与傅立叶变换相结合的信号实例分析

文章采用离散小波变换与快速傅立叶变换相结合的方法,先对原始信号进行小波分解,再对各子带信号做快速傅立叶变换,从而得到各子带上时间信号的频谱。计算机仿真的实例分析表明,该方法将小波变换和傅立叶变换的优点结合了起来。     

基于小波变换的非平稳信号瞬时频率分析方法

利用小波变换的优越时频分辨特性,对非平稳信号的瞬时频率进行了分析,给出了模拟仿真结果,并与短时傅立叶变换作比较,得出了两者对信号瞬时频率分析的适用范围及各自的优缺点。     

基于小波变换的超短脉冲相位回归

针对频率分辨光学门法(FROG)要用傅里叶变换迭代算法耗时较长不利于实时检测的缺点,及光谱相位相干直接电场重构法(SPIDER)中用传统傅里叶方法滤波过程会产生相位噪声的缺点,提出了用小波变换回归相位的方法。对FROG迹线进行时-频分析直接提取脉冲相位,从SPIDER方法的光谱干涉条纹的小波变换中直接读取相位,对两种方法的小波变换进行了数学模拟,并与傅里叶变换结果进行对比,得到:小波变换能准确地回归超短脉冲相位。最后采用SPIDER方法测量了KLM钛宝石激光器输出脉冲的光谱干涉条纹,并用小波变换和傅里叶变换重建了光谱相位,消除了窗口滤波引入的噪声,证明了方法的正确性和可靠性,更适用于超短脉冲的评价。     

基于二进小波变换的边缘保持图像插值算法

利用离散二进小波变换(DDWT)所具有的良好的多尺度边缘提取特性以及子带间的相关性,提出了基于DDWT的边缘保持图像插值算法。算法利用多尺度边缘的指数衰减规律预测损失掉的高频子带中的边缘,并利用三次样条插值算法恢复损失掉的高频子带中的非边缘信息。最后通过离散二进小波合成得到高分辨率图像。实验结果显示,该算法优于传统的双线性和双三次插值算法。对于像Lena这样的纹理较少的图像其峰值信噪比(PSNR)提高了2dB以上,而对其它图像插值的结果也有不同程度的质量改善,插值的结果更符合人的视觉系统特性。     

准联合变换相关器实现光纤缺陷检测研究

提出实现光纤缺陷检测的光电混合式准联合变换相关器系统,该系统能够克服传统联合变换相关器的频谱尺寸小的缺点,光纤检测实验表明,系统能够实现光纤的缺陷检测,并且具有比传统的联合变换相关器更高的识别能力。     

结合小波变换与相位相关的图像匹配方法

图像匹配技术是图像测量系统中的关键技术,是目标定位中最基本的方法。相位相关作为一种图像匹配技术对噪声有较高的容忍程度,检测结果与照度无关,受几何失真影响小。但该方法对旋转变化非常敏感。为解决此问题,本文提出结合小波变换和相位相关的匹配算法,该算法首先对图像进行小波分解,并对结果中的近似信号进行空域旋转校正;然后利用相位相关方法进行图像匹配,从而达到快速精确的定位。该方法在掌纹图像匹配定位中的应用证明了它的有效性。     

基于小波变换和DCT的字符图像特征抽取新方法

从特征矢量的不变性和抗噪性角度,提出了一种基于小波变换(WT)和离散余弦变换(DCT)的字符特征抽取新方法。利用圆周投影算法,把二维的字符图像转换为一维投影。基于WT和DCT的非线性变换,克服了因变形和噪声引起的一维投影的非线性变形失真。通过对识别不同大小、方向及噪声的字符仿真实验和不同特征抽取方法的对比实验,以及对工业标牌字符的识别,表明该特征抽取方法具有尺度和旋转不变性,有较好的抗噪声能力和很好的分类性能。     

基于小波分析和神经网络的模拟电路故障诊断方法

提出了一种基于神经网络和小波分析的模拟电路故障诊断的系统方法。该方法通过对电路的可测性测度计算，选择电路的最佳测试节点，然后利用小波分析作为特征提取手段提取电路的故障特征向量，经归一化和主元分析（PCA）处理后。得到最优特征向量，最后输入到神经网络实现电路故障诊断。计算机仿真结果表明该方法具有更好的故障分辨率。     

Application of Supply Current Testing to Analogue Circuits, Towards a Structural Analogue Test Methodology

This paper describes work in progress towards the development, evaluation and validation of a structural, cost effective and quantifiable analog and mixed-signal test methodology, applicable in a production test environment and based on the application of supply current testing. To enable and support the measurements at first an analog supply current monitor was realised. The monitor offers a measurement range of 50 mA, a bandwidth of 1.5 MHz and a resolution better than 1 A. Subsequently the monitor was used to carry out measurements on a mixed-signal Asynchronous Digital Subscriber Line (ADSL) ASIC, to evaluate the feasibility of the methodology. As these initial measurements provided very interesting results, the experiments towards the validation and quantification of the test methodology are now being repeated on a larger scale. The results gathered so far show the potential of the approach to enhance test quality combined with test cost reduction.     

利用动态散斑确定光学系统的傅里叶变换面位置

本文通过推导光学系统的物的傅里叶交换面位置，得出光源的成像面为物的傅里叶交换面，并提出了精确定位的具体方法。     

基于四元数小波变换域统计模型的图像去噪

图像去噪是图像处理的基本问题,四元数小波变换是1种新的多尺度分析工具.图像经四元数小波变换后,其小波系数不仅在尺度间具有相关性,而且在尺度内也具有一定的相关性.首先利用层内及层间的相关性,用非高斯分布对四元数小波系数进行建模,然后给出分类准则,把小波系数分类为重要系数和不重要系数,再用非高斯分布模型对重要系数与其邻域系...     

基于小波理论的PSD测试系统的数据分析

位敏探测器(PSD)技术作为光电技术的重要组成部分,在各学科领域得到广泛应用.随着对PSD系统信号精度的要求越来越高,要求研究出更好的去噪效果的方法.针对PSD系统信号的特性,选择db8、sym8、coif8对含噪的信号进行处理和对比,并通过MATLAB中的小波GUI软件进行数字仿真,并对仿真结果进行比较,从而得出最适...