A Haar-Fisz Algorithm for Poisson Intensity Estimation

This article introduces a new method for the estimation of the intensity of an inhomogeneous one-dimensional Poisson process. The Haar-Fisz transformation transforms a vector of binned Poisson counts to approximate normality with variance one. Hence we can use any suitable Gaussian wavelet shrinkage method to estimate the Poisson intensity. Since the Haar-Fisz operator does not commute with the shift operator we can dramatically improve accuracy by always cycle spinning before the Haar-Fisz transform as well as optionally after. Extensive simulations show that our approach usually significantly outperformed state-of-the-art competitors but was occasionally comparable. Our method is fast, simple, automatic, and easy to code. Our technique is applied to the estimation of the intensity of earthquakes in northern California. We show that our technique gives visually similar results to the current state-of-the-art.     

Benchmarking of Three-Dimensional Clifford Wavelet Functions

Specific three dimensional wavelet functions for the Continuous Wavelet Transform (CWT) in the framework of Clifford analysis are tested upon their selectivity for pointwise and directional analysis of signals. These tests are carried out on scalar benchmark signals: the infinite rod, the semi-infinite rod and the rod of finite length. It is demonstrated that the Clifford-Hermite wavelets are efficient at detecting pointwise singularities, whereas the Clifford-Morlet wavelets possess the qualifications for directional analysis of three-dimensional signals.     

NUMERICAL INVERSION OF MULTIDIMENSIONAL LAPLACE TRANSFORMS USING MOMENT METHODS

This paper develops a numerical method to invert multi-dimensional Laplace transforms. By a variable transform, Laplace transforms are converted to multi-dimensional Hansdorff moment problems so that the numerical solution can be achieved. Stability estimation is also obtained. Numerical simulations show the efficiency and practicality of the method.     

基于矩阵分析的STR荧光解谱技术

用多种荧光标记物进行STR检测时,由于荧光光谱的谱带展宽特性,各个荧光光谱之间有重叠部分,如何实现将相互重叠的各个波长上的能量有效利用起来,对提高荧光利用效率至关重要。本文给出了一种基于矩阵分析的数据处理方法,该方法在进行荧光探测前首先要对荧光谱进行光谱校正,即要得到每种所用标记染料受激发射荧光的光谱分布,根据光谱分布建立染料组合荧光信号矩阵,然后对矩阵进行归一,利用归一后的矩阵对所探测的荧光谱进行解谱,从而得到所期望的荧光谱图。理论分析和实验结果表明,该方法可以有效的利用各个波长的荧光光谱能量,并实现对不同荧光重叠谱的有效光谱解谱。     

基于小波变换测定水质中硝酸盐含量

为了测定硝酸盐与亚硝酸盐混合液中硝酸盐含量,利用硝酸盐对照液和硝酸盐与亚硝酸盐混合液的紫外吸收光谱数据进行连续小波变换,提取与硝酸盐有关的特征小波系数,实现硝酸盐含量的光谱检测。实验结果表明：用所得特征小波系数建立与浓度的线性回归方程,所取硝酸盐浓度具有良好的线性关系（r=0.9992）,平均回收率为98.59%。本法与传统的方法相比,要求条件较低,不需要物理或化学的分离,分析速度快,有望应用于在线监测污水中测定硝酸盐的含量。     

基于共聚焦显微拉曼光谱的毛竹细胞结构和成分研究

采用共聚焦显微拉曼光谱对毛竹薄壁细胞、薄壁纤维过渡细胞和纤维细胞进行研究。通过构建偏最小二乘(PLS)定量区分模型来对这三种细胞中的差异进行分析,结果表明,该区分模型的建模和交互验证决定系数(R2)分别为0.810和0.800,均方根误差(RMSE)分别为0.323和0.332。根据这一模型的回归系数,发现三种细胞的区别主要体现在1 095,1 319和1 636 cm-1三个波数,这三个波数分别为纤维素、半纤维素和木质素的指纹特征峰。以这三个波数为自变量建立多元线性回归(MLR)模型,该回归模型的建模和交互验证决定系数(R2)分别为0.644和0.643,均方根误差(RMSE)分别为0.442和0.443,表明三种细胞在这三个波数处存在明显的差异。对小波变换基线消除后的拉曼光谱信号进行化学成像分析,结果显示,纤维素微纤维与纤维轴成一个很大的角度,这一结构有利于提高细胞的弹性模量和硬度。半纤维素和纤维素微纤维通过氢键相连,并在范德华力的作用下紧密地结合在一起,因此在拉曼化学成像中可以看到半纤维素和纤维素有相似的分布规律。三种细胞的细胞角和胞间层都高度的木质化,从细胞壁外层到内层木质化程度逐渐降低,表明细胞壁的木质化从细胞角和胞间层开始,且木质化程度并不完全。     

氢气放电中X射线测量的能量刻度

在用微机多道测量氢气放电中的异常X射线能谱时,需要准确地给出各新谱线峰位的能量值,它由刻度求得的谱仪系统的零点和道数一能量转换系数给出,本文通过实验比较了能量刻度的四种方法:道数一能量关系直线外推法;脉冲幅度一道数关系直线外推法;双能X射线源法;特征X射线法.比较结果说明:用道数一能量直线外推法进行刻度最为准确,当能量大于2.0 keV时,其能量刻度不确定度小于2%.     

线性调频Z变换在舱音背景声的特征频率分析中的应用

舱音背景声特征频率的确定是调查失事飞机事故原因的重要依据之一。基于舱音译码辨听和音频分析的传统方法难以准确获得舱音背景声的特征频率。本文提出采用基于FFT的线性Z变换(CZT)来获取舱音背景声的特征频率的新方法,该方法适用于高采样频率的信号,计算中可以调整频率的分辨率,增加了FFT和频谱分析的灵活性。通过仿真和对用舱音记录器测录的真实舱音背景声计算分析得出:CZT方法是一种适合于确定舱音背景声特征频率的实用、有效方法,用以区分不同舱音在频率上的差别,满足飞机事故原因调查的需要。     

一种实用的傅里叶变换轮廓术系统校准方法

在傅里叶变换轮廓术(FTP)中,根据针孔模型透镜成像理论,在考虑摄像机的径向畸变和切向畸变的情况下,利用畸变量较小的图像中心信息,对测量系统放置位置进行调整。采用相位——高度映射并结合最小二乘法及曲线拟合对高度和畸变分别校准。该方法能够简单、快速的对摄像机系统进行标定和修正,提高了FTP测量的精度,特别是在横向坐标方向上的精度。实验验证了所提方法的正确性。     

Fast simulation of the forward tracking detector of HPLUS

The necessity of installing a forward tracking detector stack is discussed for the Hadron Physics LanzhoU Spectrometer(HPLUS). A local tracker is developed to solve the multi-track finding problem. The track candidates are searched iteratively via Hough Transform. The fake tracks are removed by a least square fitting process. With this tracker we have studied the feasibility of