Abstract
This paper investigates the adaptive anti-synchronization problem for time-delayed chaotic neural networks with unknown parameters. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality (LMI) approach, the adaptive anti-synchronization controller is designed and an analytic expression of the controller with its adaptive laws of unknown parameters is shown. The proposed controller can be obtained by solving the LMI problem. An illustrative example is given to demonstrate the effectiveness of the proposed method.
| Original language | English |
|---|---|
| Pages (from-to) | 3498-3509 |
| Number of pages | 12 |
| Journal | International Journal of Theoretical Physics |
| Volume | 48 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 2009 Dec |
| Externally published | Yes |
Bibliographical note
Funding Information:This paper was supported by Wonkwang University in 2009.
Keywords
- Adaptive control
- Anti-synchronization
- Delayed chaotic neural networks
- Linear matrix inequality (LMI)
- Lyapunov-Krasovskii stability theory
ASJC Scopus subject areas
- General Mathematics
- Physics and Astronomy (miscellaneous)