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Title |
Stability of Cohen-Grossberg Neural Networks with Impulsive and Mixed Time Delays |
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Author |
Zhenjiang Zhao, Qiankun Song |
| Citation |
Vol. 8 No. 2 pp. 94-101 |
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Abstract |
In this paper, the problem of stability analysis for a class of impulsive Cohen-Grossberg neural networks with mixed time delays is considered. The mixed time delays comprise both the time-varying and distributed delays. By employing a combination of the -matrix theory and analytic methods, several sufficient conditions are obtained to ensure the global exponential stability of equilibrium point for the addressed impulsive Cohen-Grossberg neural network with mixed delays. The proposed method, which does not make use of the Lyapunov functional, is shown to be simple yet effective for analyzing the stability of impulsive neural networks with variable and/or distributed delays. Moreover, the exponential convergence rate is estimated, which depends on the system parameters. The results obtained generalize a few previously known results by removing some restrictions or assumptions. An example with simulation is given to show the effectiveness of the obtained results. |
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Keywords |
Cohen-Grossberg neural network, global exponential stability, time-varying delays, distributed delays, impulsive effect |
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