Exponential stability of impulsive neural networks with time-varying delays

This paper considers the problems of global exponential stability for impulsive neural networks with time-varying delays, some new criteria ensuring globally exponential stability are obtained. The results obtained impose constraint conditions on the network parameters of neural system independent and are applicable to all continuous non-monotonic neuron activation functions. Compared with the previously reported results in the literature, our results obtained in this paper provide better one more set of criteria for determining the stability of neural networks with time-varying delays. Moreover, two illustrative examples will be given to demonstrate the effectiveness of our results.