一种新的单层神经网络学习算法分析模型

A New Analysis Model for the Fast Learning Algorithm for Single Layer Neural Network

提出了适用于单层神经网络快速学习算法分析的一种新模型——广义系统辨识模型，分析了Ｋａｒａｙｉａｎｎｉｓ的快速ＢＰ算法．研究结果表明：利用所提出的新模型。

The single layer NN fast learning algorithm is a gradient descent method. By adjusting the connection weights of the neural network, the value of the generalized error function for the training of neural network is a minimum. A generalized system identifying model for the single layer neural network is proposed. It is suitable for the statistical analysis of the fast backpropagation algorithm. By means of the model proposed, the mean weight behavior and generalized error of Karayiannisfast BP algorithm are investigated. It is shown that ,although the weights grow unbounded, the fast BP algorithm will perform the training quickly.