Anti-synchronization control of a class of memristive recurrent neural networks

In this paper, we formulate and investigate a class of memristive recurrent neural networks. Two different types of anti-synchronization algorithms are derived to achieve the exponential anti-synchronization of the coupled systems based on drive–response concept, differential inclusions theory and Lyapunov functional method. The proposed anti-synchronization algorithms are simple and can be easily realized. The analysis in the paper employs results from the theory of differential equations with discontinuous right-hand side as introduced by Filippov. The obtained results extend some previous works on conventional recurrent neural networks.

► A new memristive system is formulated. ► Some novel control schemes are proposed for state-dependent switching dynamical system. ► The method for the qualitative analysis of memristive system is new and efficacious. ► The approach overcomes the drawback in the literature. In addition, the robustness is taken in account.