ERBF network with immune clustering

Based on immune clustering and evolutionary programming(EP), a hybrid algorithm to train the RBF network is proposed. An immune fuzzy C-means clustering algorithm (IFCM) is used to adaptively specifythe amount and initial positions of the RBF centers according to input data set; then the RBF network is trained with EP that tends to globaloptima. The application of the hybrid algorithm in multiuser detection problem demonstrates that the RBF network trained with the algorithm has simple network structure with good generalization ability.