自学习神经元及自学习BP网络

SELF-EARNING NEURONS AND SELF LEARNING BP NETWORKS

  • 摘要: 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.

     

    Abstract: 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.

     

/

返回文章
返回