Online process mean estimation using L1 norm exponential smoothing

A basic assumption in process mean estimation is that all process data are clean. However, many sensor system measurements are often corrupted with outliers. Outliers are observations that do not follow the statistical distribution of the bulk of the data and consequently may lead to erroneous results with respect to statistical analysis and process control. Robust estimators of the current process mean are crucial to outlier detection, data cleaning, process monitoring, and other process features. This article proposes an outlier‐resistant mean estimator based on the L₁ norm exponential smoothing (L₁‐ES) method. The L₁‐ES statistic is essentially model‐free and demonstrably superior to existing estimators. It has the following advantages: (1) it captures process dynamics (e.g., autocorrelation), (2) it is resistant to outliers, and (3) it is easy to implement. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

控制不等式的改进

讨论了随机过程控制关系产生的不等式,对这个不等式给出了一个新系数,改进了以前的结果,并将其应用于局部平方可积鞅.     

二维正方点阵液态声子晶体的带隙计算

介绍了计算二维正方点阵液态声子晶体带隙的PWM法。在四氯化碳/水银复合体系中发现了完全带隙,当四氯化碳填充分数为约22%时带隙宽度达到最大值。研究了三种不同截面形状的填充物,其中,圆形截面填充物体系比方形截面及其45°旋转的体系更有利于产生宽带隙。对圆形截面填充物体系,当填充分数为f=0 229时有最宽带隙ΔΩ=0 5497。将填充物和基体交换,即水银/四氯化化碳复合体系中,所得到的带隙宽度显著减小。     

基于图像拼接技术的电子对景图制作技术?

针对当前对景图制作存在的问题，提出了一种基于图像拼接技术的电子对景图的制作技术，该技术采用SIFT算法提取海区图像的特征点，使用RANSAC算法对特征点进行精确提纯，最后使用加权平均法实现图像的平滑过渡。实验表明该技术可实现海区图像的无缝拼接，真实感强。     

内表面间垂直度的高精度测量方法设计与误差分析

针对框体类零件超精密加工的难点问题--内表面问垂直度误差的高精度测量,提出了一种基于波面干涉技术测量的新方法,建立了垂直度测量系统,分析了各调整误差对测量结果的影响.该方法能够实现框体类零件内表面间垂直度误差的高精度测量与评价,并能得到误差的三维分布,测量结果可直接用于零件的确定性修形加工.实验表明,该方法可实现0.6"的综合测量精度.     

析健全灭火救援勤务实战化的必要性

随着科技水平的不断提高，各类建筑、交通运输、化工类产品的发展和运用，消防官兵在灭火救援工作中因爆炸、触电、倒塌、辐射等种种原因而造成伤亡的事故呈直线上升趋势，这当中有许多客观因素，但这和消防部队指挥员指挥水平也有很大关系。灭火救援潜在危险因素增多，当前建立健全勤务实战化，提高灭火救援能力很有必要。     

基于偏最小二乘特征提取的支持向量机回归算法

为了提高SVM的建模质量,简化建模难度,提出了PLS-SVM组合回归建模方法.该方法通过PLS对样本数据进行降维、去噪以及消除共线性处理后,再进行SVM回归建模.不仅保持了SVM良好的模型性能,而且使SVM具备特征提取功能.实验结果表明,该方法是可行的,采用此法构建的SVM模型,泛化性能优于没有特征提取的SVM.     

基于正态分布曲线的分段式变步长LMS算法

针对传统最小均方误差(Least Mean Square, LMS)自适应滤波算法由于步长固定,在解决稳态误差与收敛性之间的关系时,始终处于矛盾状态的问题,在对传统的固定步长LMS自适应滤波算法分析的基础上,根据变步长LMS自适应滤波算法的步长调整原则,通过构造步长因子与误差信号的非线性函数,提出了一种基于正态分布曲线的分段式变步长LMS自适应滤波算法,并分析了参数取值对算法性能的影响。针对实际信号处理过程中参考信号难以选取的问题,提出了一种基于分裂阵的参考信号选取方法。理论和海试数据分析结果表明:该算法的收敛速度和稳态误差明显优于固定步长的LMS自适应滤波算法和基于Sigmoid函数的变步长LMS自适应滤波算法。     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

EU armed forces and social media: convergence or divergence?

This article explores how armed forces in EU member states work with and view social media in national and international settings, and what the patterns of convergence/divergence are on these issues. To that end, a questionnaire targeted at EU armed forces was constructed. An index of qualitative variation was calculated to explore the relative convergence among respondents (n = 25) on issues of risks and opportunities with using social media nationally and internationally. Consistent with previous research on European armed forces, we found higher levels of divergence than convergence. Contrary to our expectations that similar challenges, joint international standards, and membership in international organizations would foster convergence with regard to social media use in areas of deployment, we found that convergence appeared foremost pertaining to the domestic level. Policy divergence was strongest in areas of deployment.