Abstract
In this paper, a new sufficient condition is given for the global asymptotic stability and global exponential output stability of a unique equilibrium points of delayed cellular neural networks (DCNNs) by using Lyapunov method. This condition imposes constraints on the feedback matrices and delayed feedback matrices of DCNNs and is independent of the delay. The obtained results extend and improve upon those in the earlier literature, and this condition is also less restrictive than those given in the earlier references. Two examples compared with the previous results in the literatures are presented and a simulation result is also given.
| Original language | English |
|---|---|
| Pages (from-to) | 367-375 |
| Journal | International Journal of Neural Systems |
| Volume | 13 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Oct 2003 |
| Externally published | Yes |
Research Keywords
- Delayed cellular neural networks
- global asymptotic stability
- global exponential output stability
- equilibria
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