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Abstract: This paper analyzes the robustness of global exponential stability of delayed recurrent neural networks (DRNNs) subject to parameter uncertainty in connection weight matrices. Given a globally exponentially stable DRNNs, the problem to be addressed herein is how much parameter uncertainty in the connection weight matrices that the neural network can remain to be globally exponentially stable. We characterize the upper bounds of the parameter uncertainty for the DRNNs to sustain global exponential stability. The upper bounds of parameter uncertainty intensity are characterized by using transcendental equations. Moreover, we prove theoretically that, for globally exponentially stable DRNNs, if additive parameter uncertainties in connection weight matrices are smaller than the derived supper bounds arrived at here, then the perturbed DRNNs are guaranteed to also be globally exponentially stable. A numerical example is provided to illustrate the theoretical results. [Copyright &y& Elsevier]

Abstract: This paper analyzes the robustness of global exponential stability of recurrent neural networks subject to parameter uncertainty in connection weight matrix. Given a globally exponentially stable recurrent neural network, the problem to be addressed herein is how much parameter uncertainty in the connection weight matrix that the neural network can remain to be globally exponentially stable. We characterize the upper bounds of the parameter uncertainty for the recurrent neural networks to sustain global exponential stability. A numerical example is provided to illustrate the theoretical result. [Copyright &y& Elsevier]

Abstract: In the present paper, a new impulsive parabolic complex network (IPCN) with time-varying delays is proposed. Then, by constructing appropriate Lyapunov functionals and utilizing inequality techniques, some sufficient conditions are given to ensure that the proposed network model is globally exponentially stable. Furthermore, when the parameter uncertainties appear in the IPCN, several robust global exponential stability conditions are also presented. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of our criteria. [Copyright &y& Elsevier]