Study on the Fast Learning Algorithm of Single-layer Neural Networks
单层神经网络的快速学习算法研究

This paper proposes a new generalized criterion for the training of single layer neural networks, which leads to a novel fast learning algorithm for single layer neural network. In order to analyse the convergent properties of the fast algorithm we developed, a new generalized system identificaton model is also presented. Experiment results show that the fast algorithm proposed in this paper performs the training of neural nework faster than the corresponding learning algorithm given by Karayiannis.