曲线拟合在核探测器信号幅度提取中的应用

研究数字化核探测器输出脉冲信号的幅度提取问题。根据闪烁探测器的电路特性，推导了其脉冲信号理想曲线方程。综合利用三和值法、最小二乘法、试探法等方法，设计了该理想曲线拟合算法。由脉冲信号采样点数据，通过曲线拟合，计算出曲线的极大值，该值即为闪烁探测器输出脉冲信号的幅度。正反演数据结果对比表明，采用曲线拟合算法提取闪烁探测器输出脉冲信号幅度，其方案可行，计算结果更准确。相较于数字滤波和数字脉冲成形方法提取核探测器输出脉冲幅度，该算法更简单，对仪器的硬件处理速度要求更低。该方法开辟了核探测器脉冲幅度提取的新途径。     

一种深度图像拟合圆柱的优化方法

圆柱状构件广泛存在于古建筑仿真中,为了提高古建筑深度图像圆柱拟合的精度,针对古建筑仿真3维建模的特点,提出基于高斯图获取圆柱拟合参数初始值,然后利用圆柱距离函数参数化法进行非线性最小二乘拟合的圆柱拟合方法。实验证明,该方法不仅具有较高的精度,而且拟合结果稳定可靠。     

Best prediction in linear models with mixed integer/real unknowns: theory and application

In this contribution, we extend the existing theory of minimum mean squared error prediction (best prediction). This extention is motivated by the desire to be able to deal with models in which the parameter vectors have real-valued and/or integer-valued entries. New classes of predictors are introduced, based on the principle of equivariance. Equivariant prediction is developed for the real-parameter case, the integer-parameter case, and for the mixed integer/real case. The best predictors within these classes are identified, and they are shown to have a better performance than best linear (unbiased) prediction. This holds true for the mean squared error performance, as well as for the error variance performance. We show that, in the context of linear model prediction, best predictors and best estimators come in pairs. We take advantage of this property by also identifying the corresponding best estimators. All of the best equivariant estimators are shown to have a better precision than the best linear unbiased estimator. Although no restrictions are placed on the probability distributions of the random vectors, the Gaussian case is derived separately. The best predictors are also compared with least-squares predictors, in particular with the integer-based least-squares predictor introduced in Teunissen (J Geodesy, in press, 2006).     

Road Surface Modeling and Representation from Point Cloud Based on Fuzzy Clustering

A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automati...     

基于BP神经网络的三维激光测高数据拟合方法

针对三维激光测高拟合问题，本文采用BP神经网络进行拟合，该方法可以有效地消除或减弱数据中的系统误差影响，提高计算精度。实际算例证明，在数据无粗差情况下，BP神经网络的内符合与外符合精度优于传统的二次曲面拟合的精度。     

Relationships between rainy days,mean daily intensity and seasonal rainfall in normal,flood and drought years over india

There are limitations in using the seasonal rainfall total in studies of Monsoon rainfall climatology. A correlation analysis of the individual station seasonal rainfall with all India seasonal mean rainfall has been made. After taking the significance test (strictly up to 5% level) the stations which are significantly correlated have been considered in this study in normal, flood and drought years respectively. Analysis of seasonal rainfall data of 50 stations spread over a period of 41 years suggests that a linear relationship fits better than the logarithmic relationship when seasonal rain-fall versus number of rainy days is studied. The linear relationship is also found to be better in the case of seasonal rainfall versus mean daily intensity.     

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加权最小二乘优化倾斜摄影测量模型矢量化精度方法研究

无人机倾斜摄影测量技术以高精度、高效率、大范围的方式全面感知复杂场景,通过专业的数据采集设备和建模软件恢复三维场景,再进行量测。市场上的三维测图软件大部分是基于立面散点正交原理,不能有效地减弱人工立体测图产生的误差。本文提出一种加权最小二乘直线拟合优化倾斜摄影测量模型矢量化精度的方法,选取南昌市桑海管理委员会部分区域进行地形图数据采集和精度评定,试验表明,采用本文方法所建立的立体测图模型精度提高了2 cm。     

热带风压场平衡特征及其对GRAPES系统中同化预报的影响研究I:平衡特征分析

本文基于GRAPES全球模式的短期预报误差样本,利用赤道波动正规模态研究了热带风、压场平衡特征,并根据这些特征分析了线性平衡方程(LBE)在该区域应用时存在的问题。结果表明:(1)赤道波动能成功解释热带短期预报误差样本的大部分分量,对流层中层为60%~80%,对流层顶和平流层低层为80%以上。(2)在可解释的误差方差中,赤道罗斯贝波(ER)占比仅为30%~55%,其他赤道波动的作用不可忽视。(3)在ER模态基础上引入其他赤道波动会大幅削弱原有风、压场平衡约束,重力惯性波与Kelvin波的作用最为显著。此时,对流层中层位势高度h与u风、v风间的约束接近于零,而平流层低层h-u的平衡特征由Kelvin波主导。(4)LBE主要表达了ER模态下的风、压场平衡特征,与实际情形相比高估了热带风、压场的耦合程度,进一步的改进中需削弱这一虚假平衡,使得热带风、压场分析变得更加独立。