自学习神经元及自学习BP网络

本文针对现有人工神经元及BP网络的缺点，从 实现角度提出一种新型神经元及新型BP网络——自学习神经元及自学习BP网络．自学习神经 元的突出特点之一是它的内部有正向通道、反向通道及学习器，因而能够独立完成信息的正 向传播、误差的反向传播及神经元参数的修正．由自学习神经元组成的自学习BP网络可以真 正做到正向传播信息、反向传播误差及学习的并行化．本文还考虑了自学习BP网络的学习问 题，提出一种新的学习策略．我们的仿真结果表明这种学习策略有很好的学习效果．

SELF-EARNING NEURONS AND SELF-LEARNING BP NETWORKS

A new king of neurons and new kind if BP networks, self learning neurons and self learning BP networks, are presented in this paper with a wiew to their implementation. A self learning BP network is composed of self learning neurons. One of the prominent characteristics of the self learning neuron is thatit has a forward channel, a backward channel and a leamer, This makes each neuron in a self learning BP network accomplish the forward propagation of message, backward propagation of errors, and modification of its parameters independently, and hence makes the network implement parallel computing easity. A new training policy for BP networks is also presented in this paper. Simulation results demonstrate the effectiveness of the policy.