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1)  normalized identical distance
归一化等同距离
1.
In order to reasonably measure the difference between symbolic sequences in [0,1], this paper presents the concepts of normalized identical distance and normalized edit distance.
为了在[0,1]区间上合理度量符号序列之间的区别,提出了归一化等同距离和归一化编辑距离的概念,并通过数学分析证明了它们满足度量的3条基本公理,从理论上说明了它们的合理性。
2)  Normalized equicrual metric
等腰归一化距离
3)  Equicrural Normalized Pseudo-metric
等腰归一化伪距离
4)  normalized distance
归一化距离
1.
In the matching phrase normalized distance and Mahalanobis distance are used to identify the view class and build the affine matrix.
匹配阶段分别采用归一化距离和马氏距离作为视类判定和仿射矩阵建立的依据。
2.
In this paper,on the basis of fuzzy quotient space theory,cluster analysis methods based on fuzzy similarity relations and normalized distance are proposed to solve data structure analysis of complex systems.
在商空间理论基础上,提出了基于Fuzzy相似关系和归一化距离的聚类分析方法,用以解决复杂系统的数据结构分析问题。
5)  normalized edit distance
归一化编辑距离
1.
For the inaccuracy problem of using Euclidean and Hausdorff distances to measure the trajectories difference,a motion trajectory learning approach is developed based on the normalized edit distance and spectral clustering algorithm.
针对欧氏距离和Hausdorff距离等在描述目标运动轨迹差异性时度量不够准确的问题,提出一种基于归一化编辑距离和谱聚类的轨迹分布模式学习方法。
2.
In order to reasonably measure the difference between symbolic sequences in [0,1], this paper presents the concepts of normalized identical distance and normalized edit distance.
为了在[0,1]区间上合理度量符号序列之间的区别,提出了归一化等同距离和归一化编辑距离的概念,并通过数学分析证明了它们满足度量的3条基本公理,从理论上说明了它们的合理性。
6)  Unitary distance factor
归一化距离因子
补充资料:公理化方法(见公理化和形式化)


公理化方法(见公理化和形式化)
axiomatical method

  gongllbuafangfa公理化方法化和形式化。(axiomatieal method)见公理
  
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