A Fast Learning Algorithm of Feedforward Neural Networks and its Application to System Indentification
一种前向神经网络快速学习算法及其在系统辨识中的应用

In this paper,we propose a fast learning algorithm of feedforward networks based on the least squares.Compared with existing similar algorithms,the present algorithm does not require any matrix inversion,therefore,it has a less computational cost and can be better suited for system indentification and other areas where fast learning is required.We derive the algorithm and also give an even simpler and more convenient localized algorithm.Simulation results for system identification show the effectiveness of the algorithm.