Application of the Error Function in Analyzing the Learning Dynamics Near Singularities of the Multilayer Perceptrons
Analyzing the learning dynamics near singularities of the feedforward neural networks is a research hotspot in recent years, but the unintegrability of the log-sigmoid function make us hardly to detailed analyze the singular behaviors of the multilayer perceptrons. In this paper, the error function is adopted to the activation function of the multilayer perceptrons because of its integrability. We obtain the explicit expressions of two important expectations based on which we would easily obtain the averaged learning equations of the multilayer perceptrons and then could deeply analyzed the learning dynamics near singularities. The simulation results indicate that it is proper to use the error function to be the activation function of the multilayer perceptrons in analyzing the singular behaviors.
Singular multilayer perceptrons error function log-sigmoid
GUO Weili WEI Haikun ZHAO Junsheng LI Weiling ZHANG Kanjian
School of Automation, Southeast University, Nanjing 210096, P. R. China
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
3240-3243
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）