On the global robust asymptotic stability of BAM neural networks with time-varying delays

In this paper, the global robust asymptotic stability of a class of delayed bi-directional associative memory (BAM) neural networks, which contain variable uncertain parameters whose values are unknown but bounded, is studied. Some new sufficient conditions are presented for the global stability of BAM neural networks with time-varying delays by constructing Lyapunov functional and using linear matrix inequality (LMI), Halanay's inequality. A numerical example is presented to illustrate the effectiveness of our theoretical results.