Abstract
Some sufficient conditions for the asymptotic stability of cellular neural networks with time delay are derived using the Lyapunov-Krasovskii stability theory for functional differential equations as well as the linear matrix inequality (LMI) approach. The analysis shows how some well-known results can be refined and generalized in a straightforward manner. Moreover, the stability criteria obtained are delay-independent. They are less conservative and restrictive than those reported so far in the literature, and provide a more general set of criteria for determining the stability of delayed cellular neural networks.
| Original language | English |
|---|---|
| Pages (from-to) | 3377-3384 |
| Journal | International Journal of Bifurcation and Chaos in Applied Sciences and Engineering |
| Volume | 14 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - Sept 2004 |
Research Keywords
- Asymptotic stability
- Cellular neural networks
- Linear matrix inequality
- Lyapunov-Krasovskii stability theory
- Time delay
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