Global Stability of Cohen-grossberg Neural Network with Time-delays and Distributed Delays Via Nonlinear Measure ⋆
نویسندگان
چکیده
In this paper, the global asymptotic stability is studied for a class of Cohen-Grossberg neural networks with time-varying and distributed delays. By employing nonlinear measure and linear matrix inequality (LMI) techniques, some new sufficient conditions are obtained to ensure the existence, uniqueness of the equilibrium point and its stability for CGNNs, where the activation functions need only to be Lipschitz continuous, but not require to be bounded, monotonic or differentiable. Numerical examples are provided to illustrate the effectiveness of the results.
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