Delay-dependent H∞ synchronization for chaotic neural networks with network-induced delays and packet dropouts

This paper investigates the problem of H∞ synchronization for chaotic neural networks with network-induced delays and packet dropouts. A novel master-slave synchronization scheme is established where the network-induced delays and data packet dropouts are taken into consideration. By constructing the Lyapunov functional and employing the Wirtinger-based integral inequality, several delay-dependent conditions are obtained to guarantee that the error system is globally asymptotically stable and satisfies a prescribed H∞ performance constraint. Finally, two numerical examples are presented to validate the feasibility and effectiveness of the results derived.