Global exponential stability of high order recurrent neural network with time-varying delays

In this paper, global exponential stability of high order recurrent neural network with time-varying delay and bounded activation functions is investigated. Some improved conditions are obtained involving external input, connection weights, and time delays of recurrent neural network. Moreover, the location of the equilibrium point can be estimated. In addition, two examples are demonstrated to illustrate the effectiveness of the proposed criteria in comparison with some existing results.