Improved reliability-prediction and field-reliability-data analysisfor field-replaceable units

This paper presents a method for analyzing field-replaceable unit (FRU) field-data to obtain accurate field-reliability estimates. The estimates are used to improve reliability prediction and to prioritize the FRU that potentially need design improvement. Application of the method to a large telecommunication project reveals important differences in the age-dependent reliability estimates and the predicted constant estimate. The observed difference is used to measure the statistical bias due to special causes, and a correction term is added to obtain the improved reliability prediction model. The results of applying the priority scheme to FRU data are encouraging and show the importance of including quality-of-information in decision-making     

A survey of reliability-prediction procedures for microelectronicdevices

The author reviews six current reliability prediction procedures for microelectronic devices. The device models are described and the parameters and parameter values used to calculate device failure rates are examined. The procedures are illustrated by using them to calculate the predicted failure rate for a 64 K DRAM; the resulting failure rates are compared under a variety of assumptions. The models used in the procedures are similar in form, but they give very different predicted failure rates under similar operating and environmental conditions, and they show different sensitivities to changes in conditions affecting the failure rates     

Weibull component reliability-prediction in the presence of maskeddata

Analysts are often interested in obtaining component reliabilities by analyzing system-life data. This is generally done by making a series-system assumption and applying a competing-risks model. These estimates are useful because they reflect component reliabilities after assembly into an operational system under true operating conditions. The fact that most new systems under development contain a large proportion of old technology also supports the approach. In practice, however, this type of analysis is often confounded by the problem of masking (the exact cause of system failure is unknown). This paper derives a likelihood function for the masked-data case and presents an iterative procedure (IMLEP) for finding maximum likelihood estimates and confidence intervals of Weibull component life-distribution parameters. The approach is illustrated with a simple numerical example     

A statistical method for obtaining the factors inelectronic-component reliability-prediction models

According to US Mil-Hdbk-217, the failure rate of most electronic components can be predicted as λ_p=λ_b×π₁ ×π₂···π_n. A statistical method of obtaining these parameters is presented. The method is based on large quantities of field data, and the more current the data are, the more accurate the values of each level of λ_b and π_i. Using these values, the models in US Mil-Hdbk-217 can be applied to predict the life of electronic products. The method can also be used to verify the present values of each level of λ_b and π_i, and to provide the basis of further amendment     

基于KFCM的子空间样本选择方法

针对训练样本中包含边界样本数量的多少对支持向量机分类的精度起主要作用,提出基于核模糊C均值算法(KFCM)先对样本集进行聚类,然后利用得到的模糊隶属度矩阵计算样本的模糊熵,通过设定阈值进行子空间样本的选择,最后将得到的子空间样本作为支持向量机(SVM)的训练样本。实验结果证实,由于应用了KFCM方法克服了一些传统样本选择方法在不知道样本类别的情况下,其无法较准确地对任意形状的簇的子空间样本进行选择,同时该方法保留了典型样本,减少了训练样本的数量,从而保证了分类器的性能和较高的训练效率。通过实验比较,该方法在选取子空间样本的性能上比传统的方法要好。     

Fault simulation using small fault samples

This article emphasizes simulation-based sampling techniques for estimating fault coverage that use small fault samples. Although random testing is considered to be the primary area of application of the technique it is also suitable for estimating the fault coverage of nonrandom tests based on specific fault models. Especially for fault coverages exceeding 95%, it is shown that a precise estimate can be obtained using a fault sample of only 500 faults. The estimation is based on a binomial approximation of the probability density of the sample fault coverage. Using Bayes statistics an estimate is obtained whose accuracy is a linear function of the sample size if the fault coverage approaches 100%. The sample size is independent of the circuit size, thus making fault sampling particularly interesting for the fault simulation of ULSI designs due to the resulting reduction of the time complexity of fault simulation from O(N ₂) to O(N).This work was performed while Dr. Daehn was with the Laboratorium fuer Informationstechnologie at the university of Han- nover, Germany.     

Parametric fault detection of analog circuits based on Bhattacharyya measure

A high energy and area efficiency switching scheme for successive approximation register (SAR) analog-to-digital converter (ADC) is presented. The proposed procedure achieved 99.8% saving in switching energy and 97.4% reduction in total capacitance when applied to a 10-bit SAR ADC, compared to the conventional switching scheme. The switching energy has been calculated by taking into account both the power consumed in the switching processes and the reset energy.     

基于RSM和均匀试验的IC成品率设计方法

本文给出了一种基于均匀试验设计的响应表面模型，同时得到该模型在VLSI集成电路参数成品率中的优化方法。本方法首先对电路的关键参数进行扫描，确定满足电路基本性能时的参数变化范围。在此范围内，可对电路参数进行以数论方法为基础的均匀试验设计和建立响应表面。对拟合得到的响应表面模型进行CV拟合检验，求出最佳的电路设汁值。本方法适用于集成电路的工艺、器件和电路级的模拟。     

Parametric channel modeling based OFDM channel estimation

A simplified parametric channel estimation approach was proposed for orthogonal frequency division multiplexing （OFDM） systems. Based on parametric channel model, this algorithm is composed of two parts： the estimation of channel parameters and channel interpolation. The exponentially embedded family （EEF） criterion is exploited to determine the number of channel paths as well as the multipath time delays. Consequently, the channel frequency responses is acquired via the estimated parameters. Additionally, the authors＇ scheme is computationally efficient owing to the needless of the eigenvalue decomposition or the estimation of signal parameters by the rotational invariance technique （ESPRIT）. Simulations are provided to validate the performance of this algorithm from perspectives of the probability of correct estimation and the mean square error （MSE）. It is demonstrated that this approach exhibits a superior performance over the existing algorithms.     

Interactive image segmentation based on samples reconstruction and FLDA

Existing interactive image segmentation methods heavily rely on manual input, i.e. a sufficient quantity and correct locations of labels. In this paper, we propose a new interactive segmentation algorithm which aims to reduce human intervention and to generate high-quality segmentation results. In contrast to most energy minimizing based segmentation methods, the segmentation is cast as multi-classification in our proposed method. First, the input image is segmented into superpixels by using different methods. Then we build a dictionary consisting of all obtained superpixels and reconstruct samples represented by certain labeled superpixels. Finally, we learn a discriminative projection matrix through Fishers linear discriminant analysis (FLDA) algorithm, which learns a discriminative subspace for classification. The unlabeled superpixels are grouped into foreground or background, via calculating their minimal norm. Our method can capture long range grouping cues and reduce the sensitivity with respect to input label quantity and location of labels, by the combination of superpixels and discriminative dictionary. Extensive experiments are conducted both on MSRC and another challenging database in order to demonstrate the effectiveness of the proposed method. Quantitative and qualitative results show that our method is competitive to the state-of-the-art performance.     

基于RFID的小型天线的设计

915 MHz频段是RFID常用的频段之一,本文设计了一款该频段下工作的RFID天线,并借助ANSOFT HFSS计算软件对天线系统进行了仿真分析,通过对贴片以及接地板开槽,使天线在保持高增益的情况下,在更宽的频带上具有更好的稳定性,同时也减小了天线的尺寸,使天线整体性能更加完善。     

基于MAC的红外小目标自适应检测

针对复杂背景下的红外小目标检测,介绍了一种基于小波包变换和最小平均代价的最佳全局自适应检测算法.通过对目标图像进行小波包降噪和非线性变换对比度增强处理抑制背景杂波、提高信噪比.分析并提取了一种用于目标检测的有效特征矢量,建立并验证了目标和背景不同模式下特征矢量的分布模型.根据该模型基于最小平均代价准则解算出最佳全局自适应分割门限,从而实现红外小目标的自适应检测.仿真实验表明,小波包变换与非线性图像增强处理具有良好的降噪性能,且最佳全局自适应检测法的检测性能优越.     

小型车间信息化管理系统

提出了一种基于小型车间的信息管理系统,包括上层数据库系统、底层控制器和CAN总线通信网络3个部分。该系统能够采集机床加工检测参数和车间加工信息,然后进行存储、整理、分析和指导。通信系统采用CANBus总线,具有多主方式工作、采用非破坏性总线仲裁技术、通信方式灵活、可分不同优先级、出错率低等优点。数据库系统具有对数据的存储、整理和分析,打印输出报表和报警等功能,界面采用VisualStudio2008C#语言编写．数据库系统使用SQLServer2005。试运行证明：系统能够实现车间信息化管理要求。工作稳定,整体性能良好．能够基本满足实际生产需要。     

Detection of seizures from small samples using nonlinear dynamicsystem theory

The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D₂) of EEG time series data. In this paper, D₂ of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D₂ computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D₂ computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies     

A system for controlled microwave heating of small samples.

A system for the controlled thawing and heating of small samples in a waveguide is described. A means of maintaining constant absorbed power within the sample over a wide range of sample parameters is a major feature of the system. Provision for sensing the melting point of immersed samples is include. Samples are continuously rotated to improve heating uniformity.     

基于软件定义存储的小文件性能优化研究

针对现有技术中对小文件性能优化的效率低、运算不稳定等问题,研究出适用的解决方案。该方案基于OpenStack云平台构建软件定义对象存储系统,其中,分类合并处理模块采用分类合并方法和改进的GDS缓存替换算法,以实现缓存空间的合理分配与使用。动态预处理模块采用What-if假设方法并融合关联规则技术进行改进,提高对多种结构的小文件数据处理效率。试验表明,文中的存储系统中小文件的平均读写响应时间分别减少了32.3%和25.1%,适用性和可靠性高。     

基于局部熵的红外图像小目标检测

文中采用红外图像的局部熵变化为检测准则,确定红外图像小目标位置,对较大的红外图像目标,局部熵突变发生在目标边缘,用本方法也可确定目标边缘。文章给出了算法的实现过程,最后,用海上红外小目标真实图像进行了实验,得到了满意的结果。     

基于稀疏表示的红外小目标跟踪

针对云天背景下红外小目标跟踪易受噪声影响,传统目标模型对噪声敏感等问题,提出一种贝叶斯推理框架下使用稀疏表示建模红外小目标的跟踪算法。该算法结合目标模板向量和正负琐碎向量构建目标稀疏表示模型,在贝叶斯推理框架下使用图像子块系数向量的目标模板重构误差作为观测模型,实现小目标的跟踪。实验证明了算法的有效性和鲁棒性。     

基于小波变换的红外图像弱小目标检测研究

针对红外图像弱小点目标检测中遇到的难点,即信噪比低、帧间相对运动和强噪声干扰等问题,给出了一种帧间膨胀累积提高信噪比的方法,并且提出将l/f噪声白化和白噪声去除同步处理的新思路,大量的仿真实验证明,该方法能够很好地抑制噪声对图像的影响,大大提高信噪比,降低误检率。     

基于Wiener滤波的小目标检测方法

红外云背景中小目标检测是红外成像技术的一种典型应用。为了检测红外云背景中的弱小目标,分析了背景特性,建立了红外场景模型,提出了一种基于Wiener滤波的自适应背景抑制方法。经过去除虚假目标和目标分割,再利用目标运动的连续性和规则性进行目标检测和跟踪。对包含了仿真目标的红外云背景图像序列进行了实验,结果表明,该方法能够有效地从信噪比为2．0的背景中检测到小目标。