Pattern Classification Based On Radial Basis Function Neural Network

Radial Basis Function (RBF) neural network is a kind of forward network with good performance. It has the properties of global approximation, and has the linear relationship of output weights on the network structure. At the same time, the training speed of the network is fast. The RBF neural network also has close relation with Convolutional neural network (CNN), can avoid the local optimal problem, so the network gets more and more attention in the pattern recognition application. In this paper, the significance of RBF neural network is described, and the difference between RBF and other neural networks is introduced, and the development trend of RBF neural network is illustrated.