An adaptive activation function for multilayer feedforward neural networks

Chien Cheng Yu, Yun Ching Tang, Bin-Da Liu

研究成果: Paper

12 引文 斯高帕斯(Scopus)

摘要

The aim of this paper is to propose a new adaptive activation function for multilayer feedforward neural networks. Based upon the back-propagation (BP) algorithm, an effective learning method is derived to adjust the free parameters in the activation function as well as the connected weights between neurons. Its performance is demonstrated by the N-parity and two-spiral problems. The simulation results showed that the proposed method is more suitable to the pattern classification problems and its learning speed is much faster than that of traditional networks with fixed activation function.

原文English
頁面645-650
頁數6
出版狀態Published - 2002 十二月 1
事件2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering - Beijing, China
持續時間: 2002 十月 282002 十月 31

Other

Other2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
國家China
城市Beijing
期間02-10-2802-10-31

    指紋

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

引用此

Yu, C. C., Tang, Y. C., & Liu, B-D. (2002). An adaptive activation function for multilayer feedforward neural networks. 645-650. 論文發表於 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering, Beijing, China.