基于模糊均值聚类(Fuzzy clustering Method,FCM)理论提出大型复杂结构边界划分方法,通过建立大型复杂结构信息数据矩阵,进而确定数据中心,实现了基于FC...
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基于模糊均值聚类 Fuzzy clustering Method
模糊c均值聚类 fuzzy c-means ; Fuzzy C-Means clustering
模糊C-均值聚类 fuzzy c-mean
模糊C-均值聚类算法 C-Mean Fuzzy Clustering ; fuzzy c-means clustering ; Fuzzy C-mean Clustering Algorithm
模糊K均值聚类算法 fuzzy K means clustering algorithm
模糊C均值聚类算法 Fuzzy C-Means Clustering Algorithm ; fuzzy c means algorithm ; Fuzzy C-Means clustering
模糊尺均值聚类 fuzzy K-means cluster algorithm
模糊C均值聚类方法 fuzzy clustering method
快速模糊C均值聚类 Fast Fuzzy C-means Clustering
通过理论分析，属性均值聚类是比模糊均值聚类更稳健的聚类方法。
Attribute means clustering is more robust than fuzzy means clustering by theoretical analysis and numerical example.
这里提出了一种高效的基于模糊c均值(FCM)聚类的彩色图像分割方法，它利用塔形数据结构对彩色图像进行多层分割。
An efficient segmentation method based upon fuzzy c-means (FCM) clustering principles is proposed. The approach utilizes a pyramid data structure for the hierarchical ana - lysis of color images.
通过对模糊c均值算法聚类特性的分析，引入了约束函数及模式相似度的概念，提出了改进的FCM算法。
With the clustering feature analyzed, restrained function and pattern similarity are introduced. Then the algorithm of improved FCM is presented.
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