Gaussian fitting in gamma-ray spectral decomposition

In order to extract the information of 662-keV 137Cs spectra from the overlapping peaks with 583-keV 208Tl,609-keV 214Bi,the overlapping peaks are measured by in-situ γ-ray spectrometer using a NaI(Tl) detector.The spectral model is optimized by the Gaussian fitting algorithm,and the optimized fitting indexes for fitting/original value are from 0.96 to 0.99.Gaussian fitting verified by experiment is feasible for γ-ray spectrum analysis.The full energy peak of 137Cs is extracted correctly from the overlapping peaks,it is important for in-situ γ-ray spectrometer to estimate contamination of 137Cs in radiated environment and nuclear accident.

A Robust Indoor Localization Algorithm Based on Polynomial Fitting and Gaussian Mixed Model

Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex environment.In this paper,a robust localization algorithm based on Gaussian mixture model and fitting polynomial is proposed to solve the problem of NLOS error.Firstly,fitting polynomials are used to predict the measured values.The residuals of predicted and measured values are clustered by Gaussian mixture model(GMM).The LOS probability and NLOS probability are calculated according to the clustering centers.The measured values are filtered by Kalman filter(KF),variable parameter unscented Kalman filter(VPUKF)and variable parameter particle filter(VPPF)in turn.The distance value processed by KF and VPUKF and the distance value processed by KF,VPUKF and VPPF are combined according to probability.Finally,the maximum likelihood method is used to calculate the position coordinate estimation.Through simulation comparison,the proposed algorithm has better positioning accuracy than several comparison algorithms in this paper.And it shows strong robustness in strong NLOS environment.

Absolutely Direct Frequency Measurement of Two-Photon Transition Using Multi-Peak Fitting Approach

The optical frequency comb has been widely used in precision measurement. In this study, a multi-peak fitting approach is first proposed to fit the two-photon transition spectrum which overlaps with the neighboring transition in Rb-87. The multi-peak fitting approach is used to eliminate the frequency shift affected by the neighboring transition. With locking the carrier envelope offset frequency at 1/4 repetition frequency, the transition frequency is measured to be 770569132739.9 +/- 5.8 kHz, which agrees well with the previous result recommended by Comite International des Poids et Mesures.

Error Thresholds in Single-Peak Gaussian Distributed Fitness Landscapes

Based on the Eigen and Crow-Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gausslan distributed random variables to incorporate the effects of the fluctuations of the fitness landscapes （noise of environments） and investigate the concentration distribution and error threshold of quasispecies by performing an ensemble average within this theoretical framework. We find that a small fluctuation of the fitness landscape causes only a slight change in the concentration distribution and error threshold, which implies that the error threshold is stable against small perturbations. However, for a sizable fluctuation, quite different from the previous deterministic models, our statistical results show that the transition from quasi-species to error catastrophe is not so sharp, indicating that the error threshold is located within a certain range and has a shift toward a larger value. Our results are qualitatively in agreement with the experimental data and provide a new implication for antiviral strategies.

基于Gaussian拟合的浆纱横截面切片图像分析

为客观分析上浆纱线横截面切片图像,减少主观因素对分析结果的影响,通过对浆纱横截面切片图像灰度直方图的特征分析,提出了应用高斯(Gaussian)拟合分析灰度直方图的方法。通过对实例中高斯拟合结果主项、次项及其他项构成因素的分析,得出浆料因素在灰度直方图上的分布区间;根据该区间不同灰度概率的正态分布特征,应用3δ原则合理估计了浆料扩散范围,计算出浆纱的几何上浆率和浆料相对分布半径,所得结果与实际相符。

基于小波分析和Gaussian回归的急性低血压预测

急性低血压是危害病人健康的并发症之一,对急性低血压发生的提早预测,能够帮助医生对重症病人找到更好的医疗处理方案。提出了一个基于趋势分量的Gaussian函数拟合预测模型,即用小波多尺度分析提取出信号的趋势分量;再根据Gaussian回归模型对趋势分量进行函数拟合,得到的函数参数作为特征值,用支持向量机SVM对数据分类。Gaussian回归模型使用的是数据驱动,用系数来描述数据之间的关系。通过在较大病人数据集上实验得到了较好的效果。

基于光斑识别的角度传感器及其非线性补偿技术

为了解决现有霍尔角度传感器存在成本高、易受电磁干扰的问题,设计了一种基于光斑识别的角度传感器,将摄像头与激光发射器放置在一个密封的铝盒内,由旋转轴带动激光发射器转动,并向摄像头发射激光束,在摄像头端采集到的图像上形成不同像素的光斑,将每一个光斑中心点坐标转换为旋转轴转动的角度。采用基于最小二乘的椭圆拟合算法,对光斑中心点像素坐标进行计算。再利用高斯曲线拟合法,对输入输出曲线进行拟合,以分析传感器的非线性误差。并利用反向传播(BP)神经网络算法对传感器进行非线性补偿。实验结果表明:经BP神经网络算法补偿后,传感器的平均非线性误差为1.63、均方根误差为1.24,比未补偿前分别降低了0.61和2.56。且测量的均方误差为0.8°。

基于动态称重系统数据的车辆荷载特征分析

汽车荷载作为桥梁重要的可变荷载之一,其值的大小直接影响桥梁的安全。随着交通运输的快速发展,桥梁实际的营运荷载可能超过设计汽车荷载,在进行既有桥梁评估及加固维修时,汽车荷载的选取应反映桥梁实际的运营状况。该文基于采集的江苏省内某条高速公路350万条动态称重系统实测数据,对影响桥梁汽车荷载效应的参数进行分析,其中包括交通流的特征、车型分布、汽车总质量分布、车间距分布等。并对影响汽车荷载效应的各参数进行分布拟合,对比得到最优的拟合方案。

Gaussian process assisted coevolutionary estimation of distribution algorithm for computationally expensive problems

In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in parallel. The search space was projected into multiple subspaces and searched by sub-populations. Also, the whole space was exploited by the other population which exchanges information with the sub-populations. In order to make the evolutionary course efficient, multivariate Gaussian model and Gaussian mixture model were used in both populations separately to estimate the distribution of individuals and reproduce new generations. For the surrogate model, Gaussian process was combined with the algorithm which predicted variance of the predictions. The results on six benchmark functions show that the new algorithm performs better than other surrogate-model based algorithms and the computation complexity is only 10% of the original estimation of distribution algorithm.

基于Tail-Fit算法的抖动分离

介绍了抖动的定义和分类。提出了一种基于Tail-F it算法的抖动分离技术,给出了该算法的拟合结果,验证了算法的有效性。

基于FPGA的Gaussian传输函数实现

Gaussian函数作为RBF神经网络常用的激活函数,在FPGA上实现Gaussian函数,有利于提高神经网络的运算速度。本文简要介绍了Gaussian函数模型,并基于FPGA平台,分析了几种实现复杂函数的方案,最终采用分段拟合的方法对Gaussian函数进行逼近。首先用MATLAB对Gaussian函数进行初步的拟合,在FPGA平台用Verilog HDL语言实现Gaussian函数。仿真结果表明,误差可以控制在较小的数量级,满足神经网络运算的精度。

基于RUL和SVs-GFF的云服务器老化预测方法

针对云服务器中存在软件老化现象,将造成系统性能衰退与可靠性下降问题,借鉴剩余使用寿命(Remaining useful life,RUL)概念,提出基于支持向量和高斯函数拟合(Support vectors and Gaussian function fitting,SVs-GFF)的老化预测方法.首先,提取云服务器老化数据的统计特征指标,并采用支持向量回归(Support vector regression,SVR)对统计特征指标进行数据稀疏化处理,得到支持向量(Support vectors,SVs)序列数据;然后,建立基于密度聚类的高斯函数拟合(Gaussian function fitting,GFF)模型,对不同核函数下的支持向量序列数据进行老化曲线拟合,并采用Fréchet距离优化算法选取最优老化曲线;最后,基于最优老化曲线,评估系统到达老化阈值前的RUL,以预测系统何时发生老化.在OpenStack云服务器4个老化数据集上的实验结果表明,基于RUL和SVs-GFF的云服务器老化预测方法与传统预测方法相比,具有更高的预测精度和更快的收敛速度.

高斯函数拟合的地磁日变规律分析及改正

地磁数据的采集精度直接影响着地磁匹配定位的准确度,地磁日变改正是获取高精度地磁数据的重要前提.在远海以及一些远离台站有效范围的偏远区域设立日变站相对困难,而且保证日变站持续稳定的工作对日变站的设立提出了更高要求.日变改正步骤复杂而繁琐,大多通过多台站联合改正或监测相应时刻日变站的变化实现,对于区域地磁数据采集过程的日变改正研究相对较少.针对这些问题,文章顾及地磁静日变化存在一定周期性的特点,基于高斯拟合函数对单点位多个太阳日下的地磁场变化规律进行分析,并对区域多点的地磁场数据进行日变拟合及改正分析.试验结果表明:在一定区域范围内高斯函数拟合得到的点位磁场的静日变化能够满足地磁日变改正精度,拟合误差在几个nT以内,中误差也不超过10 nT;区域点位实验中,将高斯函数拟合获得的日变改正值与常规方法获得的日变改正值进行对比,其中82.3%的点位日变改正值的差值在±5 nT以内.因此,基于高斯函数拟合的地磁日变改正分析能够根据观测时间获得相应区域的日变改正估值,实现日变改正,获得高精度地磁数据,为地磁匹配定位提供了基础.

基于遗传-模拟退火算法修正高斯烟羽模型参数

高斯烟羽模型由于受到地形地貌与气象条件等因素的影响,难以准确反映大气的实际扩散过程。为解决上述问题,首先在经验参数作为先验值的基础上,通过遗传算法对实际观测数据进行参数反演修正,根据观测结果调整模型参数,提高模型的准确性;然后,为进一步优化参数修正结果,引入模拟退火算法,通过随机搜索和逐步降温的策略来跳出遗传算法可能陷入的局部最优解,进一步改善模型的性能。为了评估修正效果,建立一个基于权重的模型值与观测值之间差异的适应度函数,通过比较修正前后的误差率来判断参数修正对高斯烟羽模型的影响程度。仿真实验的结果表明,所提出的遗传-模拟退火算法模型能够有效地修正高斯烟羽模型中的扩散参数,修正后的模型在预测污染物浓度方面的误差率下降了89.40%。所提模型可为环境保护和污染防治提供重要的理论支撑和决策依据,具有较大的应用潜力。

基于双三次插值和高斯拟合的光条中心亚像素提取方法

针对结构光三维测量的高精度要求,提出一种基于双三次插值和高斯拟合的激光线条亚像素提取方法。该方法首先对光条图像进行感兴趣区域提取、高斯滤波等前处理,其次用形态学方法细化激光线条得到初始中心点,然后使用五点拟合法得到光条法线方向,在光条法线方向上取亚像素的拟合点,利用双三次插值得到亚像素坐标的像素值,最后进行高斯拟合,到光条亚像素中心。实验结果表明,算法平均精度值为0.389147像素,消耗时间为0.056 2 s,具有较高的提取精度和稳定性。

基于激光点云的中厚板表面平整度测量

在冶金行业中,中厚板是主要产品之一,其平整度是评估钢板质量的重要指标。压力矫平现场还依赖于人工测量,无法准确地表征板材平整度。为了提高检测的准确度及高效性,提出了一种基于机器视觉的平整度测量方法。基于高精度的三维视觉扫描技术,结合高斯拟合算法,利用高斯系数构建特征值,建立高斯特征值与实际板材弯曲高度的映射关系,构建基准平面,计算点云坐标值与基准平面的距离,结合RGB颜色模型绘制板形云图,在此基础上给出压力矫平添加垫板的位置。实验表明,所提出的方法计算误差不大于0.3 mm,可以实现对中心凸起或边缘翘曲钢板的测量,同时板形云图反映了板形分布状况及垫板位置。该度量方法可以准确测量中厚板的弯曲量,可以为压力矫平提供数据支持。

面向光纤光栅传感线性拟合度的PSO-GPR算法

【目的】为了提高光纤布拉格光栅(FBG)传感系统中反射光谱中心波长与外部环境变量之间的线性拟合度,文章提出了使用粒子群优化的高斯过程回归模型应用于FBG应力传感领域。【方法】针对FBG的反射光谱特性,文章研究了对于FBG传感系统在光谱拟合中线性拟合度的影响,通过粒子群算法去寻找高斯过程回归模型中的最优超参数以提升对反射光谱中心波长的预测性能。文章搭建了FBG应力传感实验平台,将FBG铺设在强度梁上,在等强度梁一端施加不同重量的砝码对FBG产生轴向应变,通过光谱仪采集反射光谱数据并使用文章所提模型进行线性拟合分析处理,将未优化的高斯过程回归模型、最大值法、高斯拟合法和质心法得到的结果作为对照组。【结果】结果表明,在掺铒光纤放大器输出功率为10 dBm、传输光纤距离为50 m、光谱仪采样点个数为501的条件下,反射光谱中心波长与砝码重量之间的线性拟合度均优于对照组,文章所提模型的线性拟合度最高能达到0.9519,相较于对照组均有所提升。在501、251、167和126点的光谱采样点条件下,文章所提模型能将系统的线性拟合度提升到0.9900,相较于最大值法最大提升了0.2587。【结论】分析结果表明,使用粒子群优化的高斯过程回归模型能够有效提高FBG应力传感系统的线性拟合度。

利用射电暴发信号测量系统间时延的研究

利用中国科学院国家授时中心昊平站的射电望远镜,开展基于PSR J0534+2200发射的巨脉冲信号测量两个观测系统之间时间延迟的研究。两个时间频率参考信号不同的观测系统同时对射电望远镜接收到的PSRJ0534+2200脉冲星信号进行独立观测,一共观测4次,共观测4.5h。经测量,PSR J0534+2200发射的同一巨脉冲信号在两个系统中到达时间不同,巨脉冲到达时间之差即为两个系统之间的时间延迟。采用三次样条内插法和高斯拟合法对巨脉冲的轮廓拟合,将拟合轮廓的峰值相位作为巨脉冲的到达时间。通过对测量系统时延的误差统计,结果表明:利用原始轮廓的峰值相位测量系统误差均方根小于57µs,三次样条内插法测得均方根误差小于13µs,高斯拟合法测得均方根误差小于7µs。相较于利用原始轮廓的峰值相位测量系统误差,采用三次样条内插法以及高斯拟合法对于系统延迟的精度分别提升了3.9倍和8.6倍,为利用射电暴发信号进行高精度的时间同步打下基础。

Detection of green apples in natural scenes based on saliency theory and Gaussian curve fitting

Green apple targets are difficult to identify for having similar color with backgrounds such as leaves.The primary goal of this study was to detect green apples in natural scenes by applying saliency detection and Gaussian curve fitting algorithm.Firstly,the image was represented as a close-loop graph with superpixels as nodes.These nodes were ranked based on the similarity to background and foreground queries to generate the final saliency map.Secondly,Gaussian curve fitting was carried out to fit the V-component in YUV color space in salient areas,and a threshold was selected to binarize the image.To verify the validity of the proposed algorithm,55 images were selected and compared with the common used image segmentation algorithms such as k-means clustering algorithm and FCM(Fuzzy C-means clustering algorithm).Four parameters including recognition ratio,FPR(false positive rate),FNR(false negative rate)and FDR(false detection rate)were used to evaluate the results,which were 91.84%,1.36%,8.16%and 4.22%,respectively.The results indicated that it was effective and feasible to apply this method to the detection of green apples in nature scenes.

关于阵地可探查覆盖范围的计算方法

瞬息万变的信息化战场中,实时掌握部队机动探测装备在目标区域的探测能力覆盖范围并调整决策与战备方向,对于掌控一手敌情信息有着至关重要的作用。针对以上问题,首先,根据高斯封闭曲线拟合机动探测装备的战场运动轨迹,计算探测器轨迹点距离目标区域的极小值距离;然后,绘制目标区域上下切点与部队探测器的扇形夹角;最后,完成了探测器可探查目标区域覆盖率的求解。实际应用中,采用高斯曲线拟合探测器轨迹,进而计算目标阵地可探查覆盖范围,可做到知己知彼,有利于进一步提升部队机动前出能力。