New results on exponential passivity of neural networks with time-varying delays

The problem of delay-dependent exponential passivity analysis is investigated for neural networks with time-varying delays. By use of a linear matrix inequality (LMI) approach, a new exponential passivity criterion is proposed via the full use of the information of neuron activation functions and the involved time-varying delays. The obtained results have less conservativeness and less number of decision variables than the existing ones. A numerical example is given to demonstrate the effectiveness and the reduced conservatism of the derived results.