模糊超球神经网络在模式聚类中的应用

FUZZY HYPERSPHERE NEURAL NETWORK AND ITS APPLICATION ON PATTERN CLUSTERING

提出和实现了用于模式聚类的无监督模糊超球神经网络．模式集是一个具有超球核的用隶属函数表示的模糊集，模式集又可以合并成模式类．模糊超球神经网络学习算法能在几次循环学习中形成模式集，无需对已知模式集重新训练就可融合新样例和精炼已存在的模式集．

An unsupervised hypersphere neural network that is used for pattern clustering is presented.Each clustered pattern set is a fuzzy set hypersphere with a corresponding membership function.A pattern class is the combination of the pattern sets.The center and radius of the hypersphere are determined using the fuzzy hypersphere learning algorithm,an expansion contraction process that can learn nonlinear pattern set boundaries in few passed through the data and provides the ability to incorporate new and refine existing pattern sets without retraining.The simulation of clustering demonstrates the superiority of the fuzzy hypersphere clustering neural network.