This paper introduces a newly generalized and dynamic structure for the similarity retrieval of high dimensional feature vectors called the recursive clustering index tree.
文章提出了一种新的适用于高维特征矢量相似检索动态聚类索引树结构。
In this approach, the integral operator kernel functions is used to realize the nonlinear map from the raw feature space of gear vibration signals to high dimensional feature space.
该方法通过计算齿轮振动信号原始特征空间的内积核函数来实现原始特征空间到高维特征空间的非线性映射。
The concepts of high attribute dimensional information system are firstly proposed, and a new dynamic clustering method on the basis of sparse feature difference degree is presented.
针对高属性维稀疏数据聚类问题，提出高属性维稀疏信息系统概念，给出一种新的基于稀疏特征差异度的动态抽象聚类方法。
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