Abstract
In this paper, a novel class of stochastic Cohen-Grossberg neural networks with Markovian switching (SCGNNMSs) is investigated, where the white noise and the color noise are taken into account. By utilizing Lyapunov method, some graph theory and M-matrix technique, several sufficient conditions are obtained to ensure the asymptotic boundedness of the SCGNNMSs. These criteria have a close relation to the topology property of the network and are easy to be verified in practice. Two numerical examples are also presented to substantiate the theoretical results.
| Original language | English |
|---|---|
| Pages (from-to) | 9165-9173 |
| Number of pages | 9 |
| Journal | Applied Mathematics and Computation |
| Volume | 219 |
| Issue number | 17 |
| DOIs | |
| State | Published - 2013 |
| Externally published | Yes |
Keywords
- Boundedness
- Cohen-Grossberg neural networks
- Graph theory
- M-matrix
- Markovian switching
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