A novel fuzzy clustering neural network

In this paper fuzzy clustering neural network (FCNN) is proposed with its learning algorithm, which utilizes fuzzy sets as cluster of patterns. The performance of FCNN is found better than FMN, FMPCNN, FHLSCNN and MBCNN clustering algorithms when compared with moderate number of clusters created. The cluster prototypes calculated reduces the confusion by giving fair treatment to the dense populated patterns. The total number of clusters created can be controlled by grouping factor λ. The recall time per pattern of FCNN is smaller than the FMN, FMPCNN, FHLSCNN and MBCNN. Hence it can be used for real time applications.