Research on New-CMAC with Differentiability Output and Its Learning Convergence
DOI:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In this paper, based on conventional CMAC (cerebellar model architecture controller) neural network and locally weighted regression, the improved New CMAC with the same amount of memory as that of conventional CMAC is presented, which has the conventional output and its derivative information output and hence is especially appropriate for automatic control. Accordingly, the new learning algorithm is investigated, and its learning convergence is proved.

    Reference
    Related
    Cited by
Get Citation

王士同,J. F. Baldwin, T. P. Martin.具有微分输出的神经网络New-CMAC及其学习收敛性.软件学报,2001,12(5):659-667

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:April 18,2000
  • Revised:October 17,2000
  • Adopted:
  • Online:
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063