A Reliability Growth Model

A system can be in one of two states: perfect (s0) or imperfect (s1). At any trial, the system can succeed or fail if it is in s1, but will never fail if in s0. After every failure, some corrective action is taken which, with a chance ?, will lead to a transition to s0. Even if the corrective action does not succeed, i.e. the system is still in s1, the probability of failure reduces by a constant multiple at the next trial. Expressions for the probability that the system will be in s1 at trial n and the unconditional probability that the system fails in trial n, are derived. The latter can be expressed in terms of the former. These probabilities depend not only on the number of successes in n trials but on their sequence.     

A Bayesian Reliability Growth Model

A model is presented for the change (growth) in reliability of a system during a test program. Parameters of the model are assumed to be random variables with appropriate prior density functions. Expressions are then derived that enable estimates (in the form of expectations) and precision statements (in the form of variances) to be made of: 1) projected system reliability at time ? after the start of the test program, and 2) system reliability after the observation of failure data. Numerical examples are presented, and extension to multimode failures is indicated.     

A New Test Rig for Accurate Nonparametric Measurement and Characterization of Thermoelectric Generators

Thermoelectric generators (TEGs) are increasingly employed in large-scale applications, therefore accurate performance data are necessary to permit precise designs and simulations. However, there is still no standardized method to test the electrical and thermal performance of TEGs. This paper presents an innovative test system to assess device performance in the “real world.” The fixture allows the hot temperature to be increased up to 800°C with minimal thermal losses and thermal shock; the clamping load can be adjusted up to 5 kN, and the temperatures are sensed by thermocouples placed directly on the TEG’s surfaces. A computer program controls all the instruments in order to minimize errors and to aid accurate measurement and test repeatability. The test rig can measure four TEGs simultaneously, each one individually controlled and heated by a maximum electrical power of 2 kW. This allows testing of the effects of series and parallel connection of TEGs under mismatched conditions, e.g., dimensions, clamping force, temperature, etc. The test rig can be employed both as a performance evaluator and as a quality control unit, due to the ability to provide nonparametric testing of four TEGs concurrently. It can also be used to rapidly characterize devices of different dimensions at the same time.     

Tail Extrapolation in MLSE Receivers Using Nonparametric Channel Model Estimation

This paper presents a method for determining the probability of rare events, in particular for probability density function (pdf) and bit error rate (BER) estimation. The derivation of the method is based on the presumption that the pdf is a member of a family of distributions very often named as the generalized exponential (GE) class of distributions. Based on high reliability estimations obtained in short simulation/measurement times, the low probably events are estimated accurately by extrapolation. The suggested method can be applied to some distributions that are different from GE distributions, such as noncentral chi-square distributions, to extrapolate to low probability events, with some extrapolation error. It can also be applied to BER estimation. The method is in particular helpful for estimating channels suffering from both severe signal distortion causing undesired intersymbol interference (ISI) of several symbols, and from severe noise. Such conditions prevail, for example, in metro and long haul high-speed optical fiber communication systems. So the method may be implemented in particular in maximum-likelihood sequence estimation (MLSE) optical receivers using nonparametric channel model estimation. A special use of the extrapolation method is explained for practical systems using trellis branch metrics derived from the estimated pdf to decode the transmitted sequence of symbols.     

A Reliability Growth Projection Model for One-Shot Systems

This paper offers several contributions to the area of discrete reliability growth projection. We present a new, logically derived model for estimating the reliability growth of complex, one-shot systems (i.e., the reliability following implementation of corrective actions to known failure modes). Multiple statistical estimation procedures are utilized to approximate this exact expression. A new estimation method is derived to approximate the vector of failure probabilities associated with a complex, one-shot system. A mathematically-convenient functional form for the s -expected initial reliability of a one-shot system is derived. Monte-Carlo simulation results are presented to highlight model accuracy with respect to resulting estimates of reliability growth. This model is useful to program managers, and reliability practitioners who wish to assess one-shot system reliability growth.     

A Bayes Reliability Growth Model for A Development Testing Program

The problem of estimating the reliability of a system during development is considered. The development process has several stages at each stage binomial test data are obtained by testing a number of such systems on a success/fail basis. Marginal posterior distributions are derived under the assumption that the development process constrains the reliabilities to be nondecreasing and that the prior distribution for reliability at each stage is uniform. Simulation models are designed to facilitate testing for the validity and computation of the Bayesian model with ordered reliabilities as well as to compare results with other reliability growth models.     

Nonparametric Model Comparison and Uncertainty Evaluation for Signal Strength Indoor Location

Indoor Location (IL) using Received Signal Strength (RSS) is receiving much attention, mainly due to its ease of use in deployed IEEE 802.11b (WiFi) wireless networks. Fingerprinting is the most widely used technique. It consists of estimating position by comparison of a set of RSS measurements, made by the mobile device, with a database of RSS measurements whose locations are known. However, the most convenient data structure to be used and the actual performance of the proposed fingerprinting algorithms are still controversial. In addition, the statistical distribution of indoor RSS is not easy to characterize. Therefore, we propose here the use of nonparametric statistical procedures for diagnosis of the fingerprinting model, specifically: 1) A nonparametric statistical test, based on paired bootstrap resampling, for comparison of different fingerprinting models and 2) new accuracy measurements (the uncertainty area and its bias) which take into account the complex nature of the fingerprinting output. The bootstrap comparison test and the accuracy measurements are used for RSS-IL in our WiFi network, showing relevant information relating to the different fingerprinting schemes that can be used.     

一种新型的网络安全策略模型

近年来安全模型的设计已经成为一个重要的研究课题。安全模型本质上是要满足给定系统的安全需求。文章以状态机模型为基础描述了一个简单抽象的网络安全策略模型SPM=,通过对系统在运行期间所要经历的不同阶段的安全状态讨论,给出了该模型的一个安全定理。     

一种新的信息安全体系模型的提出

信息安全的建设应该立足于一个完整的安全体系,信息安全体系模型是信息安全体系建设的基础,能够为信息安全的解决方案和工程实施提供依据和参照。文章在对现有信息安全体系模型分析研究的基础上,提出了一种新的信息安全体系模型,即P00-PDRRA模型,给出了该模型的构成框架,简述了该模型提出的意义,最后给出了一个应用实例。     

A Confidence Interval for the Barlow-Scheuer Reliability Growth Model

Barlow & Scheuer proposed a useful scheme for estimating reliability growth of a system undergoing developmental testing and offered a conservative lower s-confidence bound. This paper shows how a less conservative lower s-confidence bound can be found by using an equivalent model for system reliability.     

一种新的高阶连续的MOSFET模型

MOSFET模型一般使用不同的公式来描述不同的工作区，这使得在各工作区之间的过渡点上，模型的连续性受到限制．本文提出了一种简单有效的方法将各工作区用统一的公式来描述、它保持了原分区描述模型的精度，同时极大地改善了模型的连续性     

一种安全审计技术新模型

随着信息技术的高速发展,信息安全的"内控"问题已经到了不可忽视的地步,关键信息系统的越权操作、误操作、滥用,以及信息泄露,都有可能导致企业的重大损失,甚至危及国家安全。论文针对现有安全审计技术的不足,提出了一个有效的产品模型,试图解决目前审计产品不能审计加密协议,会话记录不完整,以及不够高效易用等问题,力图使审计产品逐渐走向实用化。     

一种汉语语音识别的新模型

本文提出了一种新的汉语语音模型-多组状态转移顺序聚类模型(MSSC).该模型采用了马尔可夫过程的状态转移方式,描述汉语语音的特征矢量序列的时序过程,同时采用了动态时间匹配DTW的比对概念和直接特征状态而不是HMM法的隐状态.新的模型具有多组子模型特点,从而对语音速度的变化,语音轻重的变化等有较强的适应能力.在描述状态转移方面,增加了记录各状态的自转移次数,用其作权重可更好地利用特征信息,提高识别率.另外,该方法的物理意义明显,故可以根据不同的特征矢量,进行合理的加权评判,且可以方便地扩充特征矢量的种类,更好的利用了汉语语音中的有用信息,进一步提高识别的正确率.本文从原理上及实际的测算结果证实了新方法的有效性.     

一种新的高频雷达海杂波的分形模型

利用分形理论建立的海杂波模型具有巨大的潜力,在高频雷达海杂波多重分形特性的基础上建立了高频雷达海杂波的时域分形模型。通过对韦布尔分布、对数正态分布、瑞利分布和K分布4种最常用的海杂波的概率密度函数的比较分析并利用修正的Kolmogorov-Smirnov(K-S)统计检验,得出了高频雷达海杂波的时域模型具有先验的统计特性的结论,证明了新的海杂波时域分形模型的合理性,这对于高频雷达海杂波建模与仿真及其背景下目标检测研究具有现实意义。     

类型强制:一种新的安全模型

首先介绍类型强制的原理,然后介绍一种纳入类型强制机制的防火墙Sidewinder。     

Nonparametric feature selection

Two groups ofL-dimensional observations of sizeN_{1}andN_{2}are known to be random vector variables from two unknown probability distribution functions [1]. A method is discussed for obtaining anl-dimensional linear subspace of the observation space in which thel-variate marginal distributions are most separated, based on a nonparametric estimate of probability density functions and a distance criterion. The distance used essentially is theL_{2}norm of the difference between Parzen estimates of the two densities. An algorithm is developed that determines the subspace for which the distance between the two densities is maximized. Computer simulations are performed.     

Nonparametric snakes.

Active contours, or so-called snakes, require some parameters to determine the form of the external force or to adjust the tradeoff between the internal forces and the external forces acting on the active contour. However, the optimal values of these parameters cannot be easily identified in a general sense. The usual way to find these required parameters is to run the algorithm several times for a different set of parameters, until a satisfactory performance is obtained. Our nonparametric formulation translates the problem of seeking these unknown parameters into the problem of seeking a good edge probability density estimate. Density estimation is a well-researched field, and our nonparametric formulation allows using well-known concepts of density estimation to get rid of the exhaustive parameter search. Indeed, with the use of kernel density estimation these parameters can be defined locally, whereas, in the original snake approach, all the shape parameters are defined globally. We tested the proposed method on synthetic and real images and obtained comparatively better results.     

Nonparametric Bayes-risk estimation

Two nonparametric methods to estimate the Bayes risk using classified sample sets are described and compared. The first method uses the nearest neighbor error rate as an estimate to bound the Bayes risk. The second method estimates the Bayes decision regions by applying Parzen probability-density function estimates and counts errors made using these regions. This estimate is shown to be asymptotically consistent in mean square. The results of experiments with these estimators on simulated and empirical data imply that the estimators both have acceptable small-sample properties; however, small-sample convergence of both estimators depends strongly on the choice of metric and local area or window size in the measurement space.     

A New Theoretical Model for Pricing Telecommunications Services

1 IntroductionThe tariff of telecommunications services is a link between the government, enterprises and customers. The government will use tariff regulation as a principal method to macro-control telecommunication enterprises. The enterprises use tariff…     

功率PIN二极管PSpice子电路模型

提出一种改进的PIN二极管子电路模型。该模型能够反映PIN二极管的瞬态开关特性,将基区电导调制效应考虑在内。通过PSpice软件瞬态仿真PIN二极管的正向直流、反向恢复特性。利用该子电路对新型SiC材料PIN二极管建模仿真,仿真结果表明运用新材料对二极管开关性能有显著提高。