Cumulative Sum Control Charts for Monitoring Weibull‐distributed Time Between Events

The Weibull distribution can be used to effectively model many different failure mechanisms due to its inherent flexibility through the appropriate selection of a shape and a scale parameter. In this paper, we evaluate and compare the performance of three cumulative sum (CUSUM) control charts to monitor Weibull‐distributed time‐between‐event observations. The first two methods are the Weibull CUSUM chart and the exponential CUSUM (ECUSUM) chart. The latter is considered in literature to be robust to the assumption of the exponential distribution when observations have a Weibull distribution. For the third CUSUM chart included in this study, an adjustment in the design of the ECUSUM chart is used to account for the true underlying time‐between‐event distribution. This adjustment allows for the adjusted ECUSUM chart to be directly comparable to the Weibull CUSUM chart. By comparing the zero‐state average run length and average time to signal performance of the three charts, the ECUSUM chart is shown to be much less robust to departures from the exponential distribution than was previously claimed in the literature. We demonstrate the advantages of using one of the other two charts, which show surprisingly similar performance. Copyright © 2014 John Wiley & Sons, Ltd.     

基于无噪后验错误矢量信号能量的变正则因子仿射投影算法

变正则因子技术是提高仿射投影自适应算法性能的重要方法之一.由于环境噪声的影响,现有的变正则因子自适应算法收敛速度较慢且稳态误差较大,各种测量、评估误差的存在进一步恶化了算法性能.为提高自适应算法的跟踪性能,本文在分析无噪先验错误矢量、无噪后验错误矢量和额外均方错误间关系的基础上,提出通过最小化无噪后验错误矢量信号能量来推导自适应变正则因子表达式的方法.在实践应用中,该方法利用了测量噪声的统计方差特性,并提出一种更加光滑且更加容易控制的指数缩放因子评估方法.系统辨识的仿真结果表明本文方法与传统的变正则因子方法以及变步长方法相比有更快的收敛速度与更低的稳态误差.     

步进电动机加速控制算法研究及仿真

针对步进电动机在启动、停止时,会出现启动失步、堵转以及超程或冲击大等现象,提出了指数加减速算法和S形曲线加减速算法。首先建立了步进电动机的数学模型和传递函数。鉴于加速启动和减速停止过程是对称的,故笔者仅研究分析了对步进电动机启动阶段进行加速控制的过程。介绍了指数加减速算法和S形曲线加减速算法原理和设计方法,并应用Matlab实现了系统设计与仿真。最后对指数加速控制和S形曲线加速控制的仿真结果进行对比分析,结果表明:与指数加减速算法相比,S形曲线加速控制方法速度过渡光滑,具有更好的动、静态性能,且易于调整和改进。     

Periodic autoregressive conditional duration

We propose an autoregressive conditional duration (ACD) model with periodic time-varying parameters and multiplicative error form. We name this model periodic autoregressive conditional duration (PACD). First, we study the stability properties and the moment structures of it. Second, we estimate the model parameters, using (profile and two-stage) Gamma quasi-maximum likelihood estimates (QMLEs), the asymptotic properties of which are examined under general regularity conditions. Our estimation method encompasses the exponential QMLE, as a particular case. The proposed methodology is illustrated with simulated data and two empirical applications on forecasting Bitcoin trading volume and realized volatility. We found that the PACD produces better in-sample and out-of-sample forecasts than the standard ACD.     

EXPONENTIAL MAP ALGORITHM FOR STRESS UPDATES IN ANISOTROPIC MULTIPLICATIVE ELASTOPLASTICITY FOR SINGLE CRYSTALS

This paper presents a new stress update algorithm for large-strain rate-independent single-crystal plasticity. The theoretical frame is the well-established continuum slip theory based on the multiplicative decomposition of the deformation gradient into elastic and plastic parts. A distinct feature of the present formulation is the introduction and computational exploitation of a particularly simple hyperelastic stress response function based on a further multiplicative decomposition of the elastic deformation gradient into spherical and unimodular parts, resulting in a very convenient representation of the Schmid resolved shear stresses on the crystallographic slip systems in terms of a simple inner product of Eulerian vectors. The key contribution of this paper is an algorithmic formulation of the exponential map exp: sl(3) → SL(3) for updating the special linear group SL(3) of unimodular plastic deformation maps. This update preserves exactly the plastic incompressibility condition of the anisotropic plasticity model under consideration. The resulting fully implicit stress update algorithm treats the possibly redundant constraints of single-crystal plasticity by means of an active set search. It exploits intrinsically the simple representation of the Schmid stresses by formulating the return algorithm and the associated consistent elastoplastic moduli in terms of Eulerian vectors updates. The performance of the proposed algorithm is demonstrated by means of a representative numerical example.     

Generators by the quadratic exponential method

Based on the quadratic exponential method, this paper constructs two types of generators over finite field Fq, the digital quadratic exponential generator and quadratic exponential pseudorandom vector generator. We investigate the distribution of the sequence generated by the generators, and present results about their one dimensional discrepancy. The proofs are based on the estimate of certain character sum over Fq. Ift is the least period of the sequence and t≥q^1/2＋2c, then the bound of the discrepancy is O（t^-1/4q^1/8＋τ logq） for any ε 〉 0. It shows that the sequence is asymptotically uniformly distributed.     

时滞双向联想记忆神经网络的全局指数稳定新条件

运用不等式αПk=1^m blk≤1/r ∑k=1^m qkbk^r＋1/rα^r（α≥0,bk≥0,qk〉0,∑k=1^m qk=r-1,r〉1）和构造新的李雅普洛夫泛函方法,研究了时滞双向联想记忆神经网络的全局指数稳定性。去掉了相关文献中有关传递函数有界性的假设,给出了较弱的并且不依赖于时滞的判别条件,增强了模型的适用性,在网络的分析和设计中发挥着重要作用。最后我们通过模拟仿真进一步说明所得结果的正确性,并对双向联想记忆神经网络的收敛速度作了分析。     

真空联合堆载预压下基于指数形式渗流的砂井地基非线性固结解

基于指数形式渗流定律,通过引入e-lgσ′和e-lgk模型来考虑土体的非线性固结特性,同时考虑了真空负压沿深度呈线性衰减的特性,对真空联合堆载预压下砂井地基的固结问题进行了求解,并推导得到了砂井地基的非线性固结解.通过将该文解析解答与已有的解析解展开对比分析,验证了该文解答的正确性.根据该文解答,对砂井地基的固结性状展...     

仿核脉冲的随机信号发生器研究

以伪均匀随机数为基础,通过算法产生高斯分布和指数分布随机数,以89C51单片计算机系统为硬件,采用Keil C编程,实现了输出脉冲幅度可以是高斯分布、指数分布及均匀分布等模式,也可以两种以上模式共同输出,输出脉冲时间间隔可以是周期性的,也可以是指数分布的。该随机信号发生器可以实现多种分布模式的输出控制,较好的仿真了核脉冲幅度和时间的随机特性。     

指数分布下无失效数据的Bayes估计

将λ的先验分布转化为pi的先验分布,并求出pi的Bayes估计,最后给出可靠度的估计.