分支前馈神经网络的研究

The Study on the Branched Feedforward Neural Network

在ＢＰ算法的基础上，提出了一种用于模式分类的人工神经网络模型——分支前馈神经网络，并给出了相应的算法。对模式分类的几个典型例子进行了计算机仿真研究。仿真结果表明，与一般ＢＰ网络相比较，分支前馈神经网络显著地减少了训练时间，且分类效果更好。

Based on the BP algorithm,the Branched Feedforward Neural Network,one ofthe artificial neural network medel used for pattern classification is proposed in this paper, and therelated algorithm is also offered here, Several typical examples of pattern classification are studiedwith computer simulation, The simulation results show that the training time of Branched Feedforward Neural Network is obviously reduced and the classifying effect is much better as compared withgeneral BP Network.