Learning efficiency improvement of fuzzy CMAC by aitken acceleration method

Chin Ming Hong, Chih Ming Chen, Hung Yu Chien

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fuzzy CMAC (FCMAC) was developed by Ker in 1997 [4] and it has advantages in terms of simple learning structure, fast convergence speed, easy implementation by hardware and the preservation of derivative information. It has been successfully applied to control field. To enhance on-line learning ability of FCMAC [7], this study presents a learning efficiency improvement approach based on Aitken acceleration method for fuzzy CMAC (FCMAC). This approach employs the forecast ability of Aitken acceleration method to shorten the training time as well as promote the learning accuracy of FCMAC. The experimental results show that the proposed Aitken acceleration method not only help FCMAC to promote the learning convergence speed, but also has more accurate learning ability than the original FCMAC.

Original languageEnglish
Title of host publication17th International Conference on Software Engineering and Knowledge Engineering, SEKE 2005
Pages556-559
Number of pages4
Publication statusPublished - 2005
Event17th International Conference on Software Engineering and Knowledge Engineering, SEKE 2005 - Taipei, Taiwan
Duration: 2005 Jul 142005 Jul 16

Other

Other17th International Conference on Software Engineering and Knowledge Engineering, SEKE 2005
CountryTaiwan
CityTaipei
Period05/7/1405/7/16

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Keywords

  • Aitken acceleration
  • Cerebellar model articulation controller
  • Fuzzy CMAC
  • Fuzzy theory
  • Prediction

ASJC Scopus subject areas

  • Software

Cite this

Hong, C. M., Chen, C. M., & Chien, H. Y. (2005). Learning efficiency improvement of fuzzy CMAC by aitken acceleration method. In 17th International Conference on Software Engineering and Knowledge Engineering, SEKE 2005 (pp. 556-559)