Adaptive synchronization between two non-identical BAM neural networks with unknown parameters and time-varying delays

In this paper, the synchronization of two non-identical bidirectional associative memory (BAM) neural networks with unknown parameters and time-varying delays is investigated. Two adaptive controllers are designed to guarantee the global asymptotic synchronization of state trajectories for two non-identical BAM neural networks. Lyapunov stability theory and Barbalat’s lemma are used to guarantee the synchronization of response and drive systems. Finally, an illustrative example is given to demonstrate the effectiveness of the presented synchronization scheme.