According to the study on the data fusion problem of multi-target tracking in wireless sensor networks,an improved fuzzy cluster mean(FCM) algorithm is proposed and the corresponding centralized fusion scheme is provided.

The analog circuits fault diagnosis based on fuzzy C-means clustering;

Segmentation of fat and lean meat in beef images based on fuzzy C-means clustering;

Brain MR image segmentation based on anisotropic Gibbs random field and fuzzy C-means clustering model;

Escaped toll analysis of ETC system customer data based on fuzzy C-means clustering;

In order to recognize the pollutant sources and build the correspondence relationships between contaminated sources and important pollutants,a set of intelligent recognizing method based on correspondence factor analysis and fuzzy C-means clustering(short for IRM-CFA&FCM) is developed.

To improve the accuracy of text clustering,fuzzy c-means clustering based on topic concept sub-space(TCS2FCM) is introduced for classifying texts.

A novel algorithm for discretization of continuous attributes in rough set theory based on FCM;

Based on the idea of combining models to improve prediction accuracy and robustness, the soft sensor model of the dry point of the first top naphtha is built by using FCM to divide a whole training dataset into several clusters with different centers.

With only pixel value information taken into account and non-robust Euclidean distance used as the distance measure standard, the classical Fuzzy C-means Clustering (FCM) algorithm lacks enough robustness in the image segmentation.

A new strategy for speaker recognition,triple-particle fuzzy C-means clustering(FCM),called TP-FCM,was proposed.

The new algorithm is based on the principle of fuzzy C-means(FCM) clustering algorithm and the transiently chaotic neural network(TCNN) algorithm.

An algorithm on data association for multisensor multitarget tracking (MSMTT) based on fuzzy comparability and fuzzy C-means (FCM)is proposed.

Therefore,based on the fuzzy C-means cluster method and the compact and separate cluster validity function,a dynamic fuzzy C-means clustering method and corresponding cluster validity function based time are put forward,and a s.

Using a modified Xie-Beni cluster validity index, the fuzzy c-means cluster algorithm with entropy regularization is extended to integrate fuzzy cluster and density estimation to identify TF components and derive TF energy mixture model that indicates the number of components in the s.

The paper based on previous studies, summing up the basic principles of Region Growing, Fuzzy C-means Cluster and BP(Back Propagation, BP) Network, using the function set and toolbox of MATLAB software, programming to separate cloud and fog on MTSAT-1R satellite image, recognizing and extracting fog areas.