关键词: 径向基, 线性分类, 线性判别式, 聚类算法

Abstract: A general and effective method is put forward to design the RBF neural network classification, which is used to recognize face in the paper. In order to avoid a fitting and reduce computation cost, the Fisher and linear discriminative technology is used to reduce dimension and extract face feature. The mixture learning algorithm is used to train RBF neural network, and so the gradient descent method is greatly reduced in search space. A new information clustering algorithm is introduced to train sample classification, and so all of the same data can be gathered together. At the same time, the compact structure RBF neural network classifier is also used to improve the algorithm. At last, the simulation experiments are done based on ORL database, and the results show that the algorithm achieves high efficiency and effectiveness.

Key words: Radial Basis Function（RBF）, linear classification, linear discriminant function, clustering algorithm