FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分-FCM algorithm is a clustering algorithm based on division, and its thinking that it is making is divided into the same cluster of the bigge

FCM Data set clustering using fuzzy c-means clustering. [CENTER, U, OBJ_FCN] = FCM(DATA, N_CLUSTER) finds N_CLUSTER number of clusters in the data set DATA. DATA is size M-by-N, where M is the number of data points and N is the number of coor

FCM+KFCM聚类分析两种方法的比较，有聚类效果图(FCM+KFCM cluster analysis of the two methods of comparison, there is a clustering effect map.)

一种快速的抗噪声模糊C均值图像分割算法 图像分割就是把图像分成若干个特定的、具有独特性质的区域并提出。该算法结合像素灰度值相似度和隶属度构造了一个新的空间函数。该空间函数用于更新成员关系，而成员关系又用于迭代地获取聚类中心。所提出的算法可以在较少的迭代次数下获得理想的分割结果，有效地降低了噪声的影响。(A fast anti noise Fuzzy C-Means Image Segmentation AlgorithmImage segmentation is to divide the i