多孔介质中可压缩混溶驱动问题的特征：混合元方法

本文考虑二维一般有界区域中的多孔介质同可压缩混溶动问题的数值解方法，给出了全离散特征－混合元格，证明了格式的唯一可解性，得到最佳Ｈ－模误差估计。     

Assessment of Uncertainty in High Frequency Data: The Observed Asymptotic Variance

The availability of high frequency financial data has generated a series of estimators based on intra‐day data, improving the quality of large areas of financial econometrics. However, estimating the standard error of these estimators is often challenging. The root of the problem is that traditionally, standard errors rely on estimating a theoretically derived asymptotic variance, and often this asymptotic variance involves substantially more complex quantities than the original parameter to be estimated. Standard errors are important: they are used to assess the precision of estimators in the form of confidence intervals, to create “feasible statistics” for testing, to build forecasting models based on, say, daily estimates, and also to optimize the tuning parameters. The contribution of this paper is to provide an alternative and general solution to this problem, which we call Observed Asymptotic Variance. It is a general nonparametric method for assessing asymptotic variance (AVAR). It provides consistent estimators of AVAR for a broad class of integrated parameters Θ = ∫ θ_t dt, where the spot parameter process θ can be a general semimartingale, with continuous and jump components. The observed AVAR is implemented with the help of a two‐scales method. Its construction works well in the presence of microstructure noise, and when the observation times are irregular or asynchronous in the multivariate case. The methodology is valid for a wide variety of estimators, including the standard ones for variance and covariance, and also for more complex estimators, such as, of leverage effects, high frequency betas, and semivariance.     

Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps

Abstract. We consider a stochastic process driven by diffusions and jumps. Given a discrete record of observations, we devise a technique for identifying the times when jumps larger than a suitably defined threshold occurred. This allows us to determine a consistent non‐parametric estimator of the integrated volatility when the infinite activity jump component is Lévy. Jump size estimation and central limit results are proved in the case of finite activity jumps. Some simulations illustrate the applicability of the methodology in finite samples and its superiority on the multipower variations especially when it is not possible to use high frequency data.     

利用最小化代价函数方法实现多窗口谱分析

利用最小化代价函数的方法推导了一种谱分析的多窗口。性能分析的结果表明，此方法与离散长球序列多窗口谱分析方法具有相当的估计偏差与方差性能。与离散长球序列多窗口相比，此方法得到的多窗口具有直观的解析表达式而无须求解矩阵的特征分解问题，因而具有较小的计算量。通过对离散白噪声与ＡＲ过程进行的多窗口谱分析对比实验，验证了此方法的有效性和正确性。     

前置中频放大器性能的改善

通信机中的收信前置中频放大器 ,其性能的高低将直接影响整机技术指标。但其性能很不稳定。通过多次实验 ,证实其原因为 :晶体管选择不合适 ;屏蔽盒尺寸选择不当。通过实验得出了改善前置中频放大器性能的方法     

小波变换思想及其在信号处理中的应用

从傅里叶变换、短时傅里叶变换到小波变换的思想发展过程中分析了小波变换发展的必然性和重要性,并通过MATLAB仿真工具比较了三种变换在信号处理中的应用。实验结果表明,小波变换无论是对信号的时间定位还是对信号的频率定位都优于傅里叶变换和短时傅里叶变换。     

一种基于冗余小波变换的DT网格运动估计和运动补偿方法

网格划分和网格顶点的运动估计是基于不规则网格的视频压缩技术的关键。为了进一步提高网格运动估计和运动补偿的效果,在综合比较现有冗余小波变换域运动估计方法和适用规则网格的EMRMC算法的基础上,提出了一种新的基于不规则网格的运动估计和运动补偿算法,即在冗余小波变换域提取特征点和运动潜在区,网格顶点的运动估计采用结合运动潜在区的在时域进行块匹配的运动估计和运动补偿方法,而运动补偿则通过三角形仿射变换完成。同时还给出了冗余小波变换域提取运动潜在区的计算模板。理论分析和实验结果表明,该算法在补偿效果方面较前两种方法得到了改进。     

单向不连续碳纤维增强热塑性树脂基复合材料弹塑性应力分析

本文采用有限元法，建立了有关的单胞模型和相关的边界条件．着重研究了单向不连续碳纤维增强聚醚醚酮复合材料的细观弹塑性应力应变关系，分析了纤维端都的不连续性对复合材料中纤维与纤维，纤维与周围基体相互作用以及应力场变化的影响．此外利用体积平均法预测了在外载荷作用下单向不连续碳纤维增强复合材料的弹塑性应力-应变关系．     

化学传感器的研究进展

化学传感器是当代信息产业的重要组成部分,其发展迅速,已在人类现代生活中发挥了重要的作用。本文介绍了化学传感器的基本概念,工作原理和分类,在此基础上着重总结了相关最新研究进展,并对化学传感器的发展做出了展望。     

A NEW SHORT EXACT GEOMETRIC CONFIDENCE INTERVAL

For discrete distributions, the standard method of producing a two‐sided confidence interval generates an interval that is exact but conservative. This paper proposes a new algorithm to produce a short exact geometric confidence interval with proven properties, and compares the new interval with the standard interval.