| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 842510 | Nonlinear Analysis: Theory, Methods & Applications | 2008 | 9 Pages |
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.
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Authors
Meiqin Liu,