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- sparse data interpolation 稀疏数据插值
- Sparse data stream found in file record segment %1. 在文件纪录段%251找到了稀疏数据流。
- Scattered in disorder data interpolation. 散乱数据插值
- In order tosolve the problem caused by sparse data two concepts of modificatory degree and modificatory distance are proposed. 为了减小数据稀疏的影响,又提出了修饰度的与修正距离的概念。
- Supervised learning with the use of regression and classification networks with sparse data sets will be explored. 也将在课程中以带有稀疏值理论的分类神经网路与回归的使用来探讨监督式学习。
- First,data interpolation and smoothness are adopted for removing absent dots and bug dots. 首先针对缺损点和毛刺点进行数据插补和平滑处理;
- A constant is given to smooth the sparse data and some handcrafting rules are used to amend the results. 对于棘手的稀疏数据问题只简单地设置平伏常数加以平滑,最后利用少量人工规则修正标注结果。
- Sinc data interpolation method is more suitable for those systems which have a stringent demand for low SNR environment and acquisition time. Sinc内插算法更适合在低信噪比下工作和对捕获时间有严格要求的系统。
- The relation between the maximum radial error and arc radius and approach step-length in the secant mode of arc data interpolation in CNC system is detailed. 并讨论了圆弧分象限“均差”割线方式插补时,圆弧的起始步距角和终止步距角、起始象限步数和终止限步数;
- It proposes a K-means type subspace clustering for supplier categorization to analyze the high dimensional and sparse data,because transaction data of supplier behavior is mass and complicated. 针对供应商行为的交易数据最大、表达复杂的特点,提出基于k-均值子空间聚类算法对供应商分类的数据挖掘方法,解决高维和稀疏数据的分析问题,并通过实例验证该方法的准确性和高效性。
- Thus a SS/OSF clustering method is proposed for high-dimensional sparse data object based on set similarity(SS) and object set feature(OSF) with the addability of object set features. 该方法基于对象组相似度(SS)和对象组特征向量(OSF),并借助对象组特征向量的可加性实现。
- This paper describes four surface modeling methods being perspective for CAD/CAMapplications,which are scattered data interpolation Gregory patch ,free-form deformation andpartial differential equation methods. 本文叙述可望在近期内进入CAD/CAM系统的4种曲面造型方法,即散列数据插值曲面、gregory的曲面构造方法(gregory曲面片)、自由变形技术(FFD)和用偏微分方程方法构造曲面(PDE)。
- We introduce and motivate the main theme of the course, the setting of the problem of learning from examples as the problem of approximating a multivariate function from sparse data - the examples. 我们介绍且激发课程的主题将朝向于实例学习法的问题设定,例如稀疏值中多变量函数近似的问题。
- Based on previous research on geostatistical data interpolation,this paper demonstrates how to use Kriging to design and implement a module to sequence and spatialize data of monitoring station. 该文在对地统计学插值方法研究的基础上,利用普通克里格法设计与实现了站点观测数据的连续空间化模型,并详细讨论了该方法的技术实现细节。最后给出系统的实现结果及用户界面。
- The fractal interpolation based on the self-similar of data interpolates data by certain mathematical model. 以分形布朗运动为基础来构造地形的相关数据可以较好地体现出地形这一具有复杂特征的自然景物的特点。
- Several methods of the data interpolating and curve fitting are introduced. 介绍了多种插值方法与曲线拟合方法,对光谱辐射照度标准灯在所需波长间隔上的照度值进行内插运算,包括这些方法的模型建立、参数计算及误差分析过程。
- A Kind of Fast Calculating Method of Sparse Data Cube 稀疏数据立方的一种快速计算方法
- The Image Reconstruction Technique of Optical CT with Sparse Data 非完全数据光学CT图像重建技术
- SS/OSF for High-Dimensional Sparse Data Object Clustering 基于SS/OSF实现高维稀疏数据对象的聚类
- The data on Argentine incomes are sparse. 有关阿根廷国民收入的资料不多。