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 language | English |
|---|---|
| Title of host publication | 17th International Conference on Software Engineering and Knowledge Engineering, SEKE 2005 |
| Pages | 556-559 |
| Number of pages | 4 |
| Publication status | Published - 2005 |
| Event | 17th International Conference on Software Engineering and Knowledge Engineering, SEKE 2005 - Taipei, Taiwan Duration: 2005 Jul 14 → 2005 Jul 16 |
Other
| Other | 17th International Conference on Software Engineering and Knowledge Engineering, SEKE 2005 |
|---|---|
| Country | Taiwan |
| City | Taipei |
| Period | 05/7/14 → 05/7/16 |
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Keywords
- Aitken acceleration
- Cerebellar model articulation controller
- Fuzzy CMAC
- Fuzzy theory
- Prediction
ASJC Scopus subject areas
- Software