贵金属纳米粒子的制备、结构和应用

贵金属纳米粒子因其特有的光学以及化学和催化性能,正引起科技界越来越浓厚的兴趣.通常这些特性决定于这些金属粒子的粒径和形态.由于非球形粒子比各向同性的球形粒子具有更优越的性能,它们已经成为研究的焦点,人们正在努力寻找粒子形状如何影响粒子理化性能的答案.贵金属纳米粒子的形状可控合成技术已经取得了明显进展.本文就贵金属纳米粒子的形状可控合成及其应用研究的当前进展进行综合评述.     

声目标识别技术研究

本文对声目标识别的关键技术进行研究,探讨用小波分析来进行声信号处理和特征提取,用BP神经网络和支持向量机的模式分类方法来进行分类识别.通过对四种声信号的仿真实验表明,使用小波变换和人工神经网络技术及支持向量机分类技术相结合对声目标进行识别是有效、可行的.     

基于非参数贝叶斯推断的MPSK信号调制识别(英文)

依据星座图采用非参数贝叶斯方法对多元相移键控(MPSK)信号进行调制识别.将未知信噪比(SNR)水平的MPSK信号看成复平面内多个未知均值和方差的高斯分布依照一定的比例混合而成,利用非参数贝叶斯推断方法进行密度估计,实现对MPSK信号分类目的.推断过程中,引入Dirichlet过程作为混合比例因子的先验分布,结合正态逆Wishart(NIW)分布作为均值和方差的先验分布,根据接收信号,利用Gibbs采样的MCMC(Monte Carlo Markov chain)随机采样算法,不断调整混合比例因子、均值和方差.通过多次迭代,得到对调制信号的密度估计.仿真表明,在SNR>5 dB,码元数目大于1 600时,2/4/8PSK的识别率超过了95%.     

基于数字图像处理的车牌识别系统的研究

基于数字图像的车牌识别技术,是一种智能的无源型车牌识别方法,在车牌没有任何信号传输设备的情况下,能够对车辆进行非接触式的固定的车辆信息采集以及实时智能识别运动状态的车牌号码.通过对多幅车牌图像的检测识别表明该技术是有效的.     

约束独立分量分析在无线通信信号分离中的应用

无线通信信号的调制方式识别是复杂电磁环境下频谱检测和频率控制的重要研究目标,为了实现频谱共存条件下调制信号的模式识别,通过利用范围区间和灵敏度参数构造参考信号,提出了一种带参考信号约束的独立分量分析(CICA)算法进行无线通信信号分离,实验仿真表明CICA算法能够很好地分离出感兴趣的信号,在0dB信噪比下分离信号和源信号的相似系数高于60%,与传统ICA方法相比,分离效果有了明显的提升。     

基于时域正则化共空间模式的单次脑电情绪识别(英文)

通过使用单次提取脑电信号的分类技术进行情绪词的脑电(EEG)识别研究.以中文情绪双字词为实验材料,通过其诱发的EEG信号,对正性词与中性词、负性词与中性词分别进行分类.使用时域正则化的共空间模式对单次提取脑电信号进行特征提取,并利用线性判别分析方法进行特征分类,分类准确率集中于55%~65%.置换检验验证了实验分类准确率的统计学显著性,表明了情绪词和中性词的成功识别,也有效地证实了基于脑电信号的语言情绪信息的可识别性.此外,在15名被试中,10名被试的负性词与中性词识别率显著,而仅有4名被试的正性词与中性词识别率显著,说明负性情绪更易被识别.     

非平稳随机激励下结构模态识别的小波协整方法

提出一种环境激励下的模态识别方法.具体方法是通过对非平稳随机激励下的线性时不变系统的结构响应进行小波变换,对各级小波系数利用协整理论进行线性合成得到新的信号.若此信号是平稳的,则以它代替原始的结构响应,然后结合平稳随机激励下的模态识别方法--NExT方法和修正的连续最小二乘法,只通过输出信号就可以实现对非平稳随机激励下系统模态参数的识别.仿真结果表明,该方法可以极大程度上消除非平稳随机激励所引起的结构响应的非平稳性,而且具有很高的精度和稳健性.     

新型二维发散波电磁粒子速度计的设计与应用

发散波作用下粒子速度的二维电磁测试关键技术包括恒定强磁场、动态载荷与磁场同步、交叉干扰项信号消除等.研究并设计了米级尺度的Helmholtz线圈,对Helmholtz线圈施加脉冲电流,获得了持续时间8.26～30.62 ms的恒定磁场平台,峰值波动误差为0.1％～1.0％.设计了新型二维发散波电磁粒子速度计,采用“对称双S型”布局感应线圈,消除干扰项,获取有效的微弱信号.有机玻璃样品中粒子速度的一维和二维电磁测试对比实验结果表明:粒子速度首峰值随爆心距的变化关系、信号时间特性符合物理规律.为有分界面、沟槽或节理的非均匀分层介质中发散波传播规律研究提供了有效的测试手段.     

微生物对裂隙岩样渗透系数的影响

选取球形芽孢杆菌单独、与原油共混以及与铜绿假单胞菌共同作用下对裂隙岩样渗透系数的影响,研究了该细菌在不同条件下的生长和沉积特性。以乙酸钙为钙源及5种钙离子浓度对细菌诱导碳酸钙沉积率的影响,优选出最佳沉积条件。采用菌液注射法对岩样裂隙进行充填实验。结果表明,水压在0. 2～0. 6 MPa时,球形芽孢杆菌单独诱导Ca2+沉积作用30 d后,岩样渗透系数可下降56%～78%;原油存在条件下,球形芽孢杆菌诱导Ca2+沉积相同时间,岩石渗透系数下降30%左右,表明原油对球形芽孢杆菌诱导Ca2+沉积具有一定的抑制作用;球形芽孢杆菌与铜绿假单胞菌同时作用下,裂隙岩石渗透系数降低30%～60%,即两种细菌同时作用的充填效果低于单一细菌作用时的填充效果。微观测试结果表明,细菌诱导碳酸钙沉积物为团簇状的絮状物,由方解石和球文石组成。     

表面肌电信号的多重分形特性分析与手势识别

为改善表面肌电信号手势识别的抗噪性和分类识别率,提出了一种基于多重分形特征的表面肌电信号手势识别方法.该方法首先借助多重分形测度分析手段,研究了不同手势动作下表面肌电信号的多重分形特性,根据不同手势表面肌电信号的多重分形谱之间的差异,提出了多重分形特征的提取算法,并利用多重分形特征结合支持向量机进行了手势识别.实验研究表明,上臂肌肉的表面肌电信号具有显著的多重分形特性,最大、最小概率子集分形维数差等多重分形特征可以作为不同手势动作的分类识别的有效特征,所提出的方法具有良好的分类识别性能,是一种有效的分类识别方法.     

A New Statistic to Assess Fitness of Cubic-Spline Postsmoothing

In equating, smoothing techniques are frequently used to diminish sampling error. There are typically two types of smoothing: presmoothing and postsmoothing. For polynomial log-linear presmoothing, an optimum smoothing degree can be determined statistically based on the Akaike information criterion or Chi-square difference criterion. For cubic-spline postsmoothing, visual inspection has been an important tool in choosing such optimum degrees in operational settings. This study introduces a new statistic for assessing the fitness of the cubic-spline postsmoothing method, which accommodates three conditions: (1) one standard error band, (2) deviation from unsmoothed equivalents, and (3) smoothness. A principal advantage of the new statistic proposed in this study is that an optimum degree of smoothing can be selected automatically by giving consistent amount of attention to deviation and smoothness across multiple equatings, whereas visual inspection may not be consistent.     

一种基于科学计算器的方差分析计算方法

利用科学计算器直接计算出总标准差和总方差以及处理标准差和处理方差,然后用方差乘以自由度得到二者的平方和,再根据平方和公式计算出误差的平方和及方差。该方法在计算程序上比传统方法更简便,可用于统计计算和教学。     

Using the Standardized Root Mean Squared Residual (SRMR) to Assess Exact Fit in Structural Equation Models

We examine the accuracy of p values obtained using the asymptotic mean and variance (MV) correction to the distribution of the sample standardized root mean squared residual (SRMR) proposed by Maydeu-Olivares to assess the exact fit of SEM models. In a simulation study, we found that under normality, the MV-corrected SRMR statistic provides reasonably accurate Type I errors even in small samples and for large models, clearly outperforming the current standard, that is, the likelihood ratio (LR) test. When data shows excess kurtosis, MV-corrected SRMR p values are only accurate in small models (p = 10), or in medium-sized models (p = 30) if no skewness is present and sample sizes are at least 500. Overall, when data are not normal, the MV-corrected LR test seems to outperform the MV-corrected SRMR. We elaborate on these findings by showing that the asymptotic approximation to the mean of the SRMR sampling distribution is quite accurate, while the asymptotic approximation to the standard deviation is not.     

B-Z化学振荡实验的时域和频域分析

B-Z化学振荡实验中数据的时域和频域分析是该实验的重点和难点。基于统计学理论,在时域上定义了反应起点至进入振荡周期的时间为振荡诱导期tin、完成一次振荡循环所需时间为振荡周期tp和电位的极差值为振幅A,并论述了标准偏差、相对标准偏差及振荡平衡点的物理化学意义。采用离散Fourier变换将时域谱变换为频域谱(振幅谱和功率谱)进行分析。结果表明:在频域谱中共有7个对称的"反应峰",零频率对应的峰是由于变换过程中的数据个数有限造成的零频率峰值;而负频率3个峰是数学处理造成的没有意义的"副产品"。正频率的3个"反应峰"分别对应了B-Z振荡反应的3个主要反应,它们的特征频率和振幅值可以清晰分辨并准确得到,其中功率谱分辨率更高一些。     

Simulation of Automotive Engine Phase Signal Based on Closed-Loop Strategy

In this paper, an automotive engine phase signal simulation algorithm is proposed based on a closed-loop feedback strategy, and its corresponding model is built. The signal incentives are carried out in the front-end, and the synchronization capture and comparison are conducted in the back-end. The phase simulation of signal output is achieved using closed-loop strategy, which can effectively eliminate the inconsistency between crankshaft and camshaft phases, and thus the accuracy and flexibility of phase signal generation are guaranteed. Experimental results show that the proposed algorithm is real time, and the deviation of simulated signals from actual phase signals is small.     

新型驱动相位控制技术提高硅微机械陀螺仪稳定性的方法

为了增强硅微机械陀螺仪的零偏稳定性,减少其受温度的影响,从数字信号处理的角度提出了一种提高驱动模态驱动相位精确度的方法.通过零偏信号生成的原理,分析出驱动相位的偏差是影响其性能的主要因素.采用基于FPGA数字信号处理实现方式的锁相环闭环控制原理,实现了对驱动相位的精确控制.给出了一种抑制相位误差的解调方法.对比模拟电路,新型数字电路很好地抑制了零偏的漂移,零偏稳定性由60°/h 提高到19°/h.新的数字控制方法显著提高了对驱动相位的控制精度,达到了增强零偏稳定性的目的.     

Introducing the mean absolute deviation ‘effect’ size

This paper revisits the use of effect sizes in the analysis of experimental and similar results, and reminds readers of the relative advantages of the mean absolute deviation as a measure of variation, as opposed to the more complex standard deviation. The mean absolute deviation is easier to use and understand, and more tolerant of extreme values. The paper then proposes the use of an easy to comprehend effect size based on the mean difference between treatment groups, divided by the mean absolute deviation of all scores. Using a simulation based on 1656 randomised controlled trials each with 100 cases, and a before and after design, the paper shows that the substantive findings from any such trial would be the same whether raw-score differences, a traditional effect size like Cohen's d, or the mean absolute deviation effect size is used. The same would be true for any comparison, whether for a trial or a simpler cross-sectional design. It seems that there is a clear choice over which effect size to use. The main advantage in using raw scores as an outcome measure is that they are easy to comprehend. However, they might be misleading and so perhaps require more judgement to interpret than traditional ‘effect’ sizes. Among the advantages of using the mean absolute deviation effect size are its relative simplicity, everyday meaning, and the lack of distortion of extreme scores caused by the squaring involved in computing the standard deviation. Given that working with absolute values is no longer the barrier to computation that it apparently was before the advent of digital calculators, there is a clear place for the mean absolute deviation effect size (termed ‘A’).     

ACCURACY OF SHORT-CUT ESTIMATES FOR STANDARD DEVIATION

The accuracy of short-cut estimates of standard deviation was investigated for distributions of raw scores on classroom tests and computer generated samples. Estimates proposed by Mason and Odeh, Jenkins, Diederich, Ebel, and Davenport were compared for relative accuracy in three studies. The loss in accuracy due to short-cut methods versus the conventional statistic ranged from 0 to 7,8%. Based on the findings of these studies, it is recommended that a shortcut method for computing standard deviations he included in courses where the conventional formula is taught.     

Maximum Likelihood Estimation of Structural Equation Models for Continuous Data: Standard Errors and Goodness of Fit

Classical accounts of maximum likelihood (ML) estimation of structural equation models for continuous outcomes involve normality assumptions: standard errors (SEs) are obtained using the expected information matrix and the goodness of fit of the model is tested using the likelihood ratio (LR) statistic. Satorra and Bentler (1994) introduced SEs and mean adjustments or mean and variance adjustments to the LR statistic (involving also the expected information matrix) that are robust to nonnormality. However, in recent years, SEs obtained using the observed information matrix and alternative test statistics have become available. We investigate what choice of SE and test statistic yields better results using an extensive simulation study. We found that robust SEs computed using the expected information matrix coupled with a mean- and variance-adjusted LR test statistic (i.e., MLMV) is the optimal choice, even with normally distributed data, as it yielded the best combination of accurate SEs and Type I errors.     

The General Nature and Applicability of Index Numbers for Education

The performances of predictive discriminant analysis (PDA) and logistic regression (LR) for the 2-group classification problem were compared. The authors used a fully crossed 3-factor experimental design (sample size, group proportions, and equal or unequal covariance matrices) and 2 data patterns. When the 2 groups had equal covariance matrices, PDA and LR performed comparably for the conditions of both equal and unequal group proportions. When the 2 groups had unequal covariance matrices (4:1, as implemented in this study) and very different group proportions, PDA and LR differed somewhat with regard to the classification error rates of the 2 groups, but the classification error rates of the 2 methods for the total sample remained comparable. Sample size played a relatively minor role in the classification accuracy of the 2 methods, except when LR was used under relatively small sample-size conditions.