基于选权迭代法的抗差整体最小二乘及其应用

在测量数据处理中,观测向量与系数矩阵同时存在偶然误差时,整体最小二乘法能够得到更高精度的参数解,但整体最小二乘法无抗差能力,观测向量中的粗差将对参数求解产生较大影响。为解决上述问题,采用拉格朗日极值法推导了基于选权迭代法的抗差整体最小二乘计算公式,通过三维坐标转换参数求解实例对3种选权迭代法进行分析。结果表明,IGG法在抗差整体最小二乘解法中抗差效果最好。     

基于土壤墒情抗差的降雨径流预报模型——设计与实验流域应用

本文旨在将实时监测得到的土壤墒情转化为流域水文模型可以直接使用的土壤含水量,论证将实时土壤墒情资料用于实时预报的可行性;利用实时监测土壤墒情,改进传统的模型结构,设计基于实测土壤墒情的降雨径流水文预报模型.采用土壤含水量误差抗差估计技术以抵御观测资料粗差的影响,提高系统的稳定性;并在此基础上提出了土壤含水量系统响应修正方法,以提高模型计算精度.将该模型应用于实验流域——宝盖洞流域进行应用检验,洪水模拟合格率达到92.3%,整体模拟精度达到甲级.     

基于移动窗口的抗差Chebyshev多项式拟合探测与修复单频GPS周跳

由于载波相位的双差观测量消除了公共误差而具有较好的平滑性,并且在双差观测序列进行相邻历元间求差后,周跳能真实地以粗差形式反映出来,在利用Chebyshev多项式拟合双差观测量时,顾及抗差估计的思想、Chebyshev多项式拟合阶数、拟合弧段长度,提出基于移动窗口的抗差Chebyshev多项式拟合算法来探测与修复周跳,分别应用采样间隔为60 s和15 s的L1频率的载波相位数据测试表明：该算法可有效探测多历元间隔周跳及连续周跳,并能对周跳进行准确的修复。     

Parameter-dependent vibration-attenuation controller design for electro-hydraulic actuated linear structural systems

The problem of robust active vibration control for a class of electro-hydraulic actuated structural systems with time-delay in the control input channel and parameter uncertainties appearing in all the mass,damping and stiffness matrices is investigated in this paper.First,by introducing a linear varying parameter,the nonlinear system is described as a linear parameter varying(LPV)model.Second,based on this LPV model,an LMI-based condition for the system to be asymptotically stabilized is deduced.By solving these LMIs,a parameter-dependent controller is established for the closedloop system to be stable with a prescribed level of disturbance attenuation.The condition is also extended to the uncertain case.Finally,some numerical simulations demonstrate the satisfying performance of the proposed controller.     

基于参数灵敏度最小的鲁棒主动控制方法

本文建立了带有参数摄动的结构状态空间模型。在此基础上，提出了基于参数灵敏度最小的鲁棒极点配置的主动控制算法，通过使闭环系统的特征值对系统参数变化不敏感来提高结构控制系统对参数摄动的鲁棒性。最后对一个单自由度结构地震作用下的控制仿真计算，证实了这种控制方法的有效性和较强的鲁棒性。     

Summary statistics in geochemistry: A study of the performance of robust estimates

Numerical data summaries in many geochemical papers rely on arithmetic means, with or without standard deviations. Yet the mean is the worst average (estimate of location) for those extremely common geochemical data sets which are non-normally distributed or include outliers. The widely used geometric mean, although allowing for skewed distributions, is equally susceptible to outliers. The superior performance of 19 robust estimates of location (simple median, plus various combined, adaptive, trimmed, and skipped,L, M, andW estimates) is illustrated using real geochemical data sets varying in sources of error (pure analytical error to multicomponent geological variability), modality (unimodal to polymodal), size (20 to >2000 data values), and continuity (continuous to truncated in either or both tails). The arithmetic mean tends to overestimate location of many geochemical data sets because of positive skew and large outliers; robust estimates yield consistent smaller averages, although some (e.g., Hampel's and Andrew's) do perform better than others (e.g., Shorth mean, dominant cluster mode). Recommended values for international standard rocks, and for such important geochemical concepts as average chondrite, can be reproduced far more simply via robust estimation on complete interlaboratory data sets than via the rather complicated and subjective methods (e.g., laboratory ratings) so far used in the literature. Robust estimates also seem generally less affected by truncation than the mean; for example, if values below machine detection limits are alternatively treated as missing values or as real values of zero, similar averages are obtained. The standard (and mean) deviations yield consistently larger values of scale for many geochemical data sets than the hinge width (interquartile range) or median absolute deviation from the median. Therefore, summaries of geochemical data should always include at least the simple median and hinge width, to complement the often misleading mean and standard deviation.     

Conditioning of the stationary kriging matrices for some well-known covariance models

In this paper, the condition number of the stationary kriging matrix is studied for some well-known covariance models. Indeed, the robustness of the kriging weights is strongly affected by this measure. Such an analysis can justify the choice of a covariance function among other admissible models which could fit a given experimental covariance equally well.     

Relative Efficiency of Single-Outlier Discordancy Tests for Processing Geochemical Data on Reference Materials and Application to Instrumental Calibrations by a Weighted Least-Squares Linear Regression Model

Numerous studies report geochemical data on reference materials (RMs) processed by outlier-based methods that use univariate discordancy tests. However, the relative efficiency of the discordancy tests is not precisely known. We used an extensive geochemical database for thirty-five RMs from four countries (Canada, Japan, South Africa and USA) to empirically evaluate the performance of nine single-outlier tests with thirteen test variants. It appears that the kurtosis test (N15) is the most powerful test for detecting discordant outliers in such geochemical RM databases and is closely followed by the Grubbs type tests (N1 and N4) and the skewness test (N14). The Dixon-type tests (N7, N8, N9 and N10) as well as the Grubbs type test (N2) depicted smaller global relative efficiency criterion values for the detection of outlying observations in this extensive database. Upper discordant outliers were more common than the lower discordant outliers, implying that positively skewed inter-laboratory geochemical datasets are more frequent than negatively skewed ones and that the median, a robust central tendency indicator, is likely to be biased especially for small-sized samples. Our outlier-based procedure should be useful for objectively identifying discordant outliers in many fields of science and engineering and for interpreting them accordingly. After processing these databases by single-outlier discordancy tests and obtaining reliable estimates of central tendency and dispersion parameters of the geochemical data for the RMs in our database, we used these statistical data to apply a weighted least-squares linear regression (WLR) model for the major element determinations by X-ray fluorescence spectrometry and compared the WLR results with an ordinary least-squares linear regression model. An advantage in using our outlier procedure and the new concentration values and uncertainty estimates for these RMs was clearly established.     

深海拖缆勘探导航数据预处理方法

深海拖缆勘探导航测量的数据质量差,出现粗差的可能性大,数据预处理过程(主要包括粗差探测、滤波平滑和数据历元化等)是数据处理的重点和难点之一。文中探讨并设计了一种预处理方法:首先通过稳健估计拟合曲线的方法探测粗差;然后滤波平滑削弱观测噪声的影响,同时进一步处理残留粗差得到较"干净"的观测值;最后进行历元化内插得到各历元时刻的观测值,为数据处理做好准备工作。     

抗差部分岭估计及其在GPS快速定位中的应用

针对GPS快速定位中观测资料含有粗差且因观测信息不足造成设计阵“部分病态”的实际情况,对现有的抗差有偏估计进行改进,提出了一种新的抗差有偏估计——抗差部分岭估计,并讨论了抗差部分岭估计中“部分岭参数”的选择方法。计算结果显示,新估计与现有的抗差有偏估计相比,具有精度高、速度快、稳定性好的特点。