Global exponential stability for reaction–diffusion recurrent neural networks with multiple time-varying delays

الملخص EN

In this paper, we consider the problem of exponential stability for recurrent neural networks with multiple time-varying delays and reaction–diffusion terms.

The activation functions are supposed to be bounded and globally Lipschitz continuous.

By means of Lyapunov functionals, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network.

Finally, a numerical example is given to show the correctness of our analysis.