Adaptive synchronization of memristor-based BAM neural networks with mixed delays

This paper investigates the adaptive synchronization of memristor-based BAM neural networks (MBAMNNs) with discrete delay and distributed delay (mixed delays). We design two kinds of adaptive feedback controllers, under which the considered MBAMNNs can achieve asymptotic synchronization and exponential synchronization respectively. The adaptive feedback controllers can be utilized even when there is no perfect knowledge of the system parameters. Furthermore, computing algebraic conditions and solving linear matrix inequalities are not needed to determine suitable control gains. Numerical simulations illustrate the effectiveness of the theoretical results.