Exponential stability of Cohen-Grossberg neural networks
Neural Networks
New conditions on global stability of Cohen-Grossberg neural networks
Neural Computation
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In this paper, we study the Cohen-Grossberg neural networks with variable coefficients and time-varying delays. By applying the Young inequality technique, Dini derivative and introducing many real parameters, estimate directly the upper bound of solutions. We will establish new and useful criteria on the boundedness and global exponential stability. The results obtained in this paper extend and generalize the corresponding results existing in previous literature.