Abstract
The global asymptotic stability of discrete-time Cohen-Grossberg neural networks (CGNNs) with or without time delays is studied in this paper. The CGNNs are transformed into discrete-time interval systems, and several sufficient conditions for asymptotic stability for these interval systems are derived by constructing some suitable Lyapunov functionals. The conditions obtained are given in the form of linear matrix inequalities that can be checked numerically and very efficiently by using the MATLAB LMI Control Toolbox. Finally, some illustrative numerical examples are provided to demonstrate the effectiveness of the results obtained.
| Original language | English |
|---|---|
| Pages (from-to) | 2403-2411 |
| Number of pages | 9 |
| Journal | Nonlinear Analysis, Theory, Methods and Applications |
| Volume | 69 |
| Issue number | 8 |
| DOIs | |
| State | Published - 15 Oct 2008 |
| Externally published | Yes |
Keywords
- Cohen-Grossberg neural network
- Discrete time
- Global asymptotic stability
- Interval system
- Linear matrix inequality (LMI)
- Time-delay system
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