Abstract：Because the feedforward neural network has an ability of approach to arbitrary nonlinear mapping, it can be used effectively in the modeling and controlling of nonlinear system. In order to improve the learning efficiency and stability of feedforward neural network, a fast learning algorithm for neural networks base on CGM-OC approach is presented. Compared with other learning methods such as BP method, Broyden Flecher Goldfarl Shanno method. Power method etc., simulation results show that the proposed method is an efficient and fast method.
郑建国; 刘芳; 焦李成. 基于正交校正共轭梯度法的快速神经网络学习算法研究[J]. 电子与信息学报, 2002, 24(5): 667-670 .
Zheng Jianguo; Liu Fang; Jiao Licheng . Study of fast learning algorithm for neural networks base on CGM-OC approach. , 2002, 24(5): 667-670 .
2002, Vol. 24 
