Analysis Of Global Asymptotic Stability Of Delayed Recurrent Neural Networks

In this paper, the global asymptotic stability and the existence of equilibrium are considered for a general class of recurrent neural networks with delays by using nonsmooth analysis and Lyapunov methods. New criteria are obtained, which does not require the boundedness of activation functions and the symmetry of the connection matrices. An example is given to illustrate the effectiveness of the results.