Global exponential synchronization of complex dynamical networks with memristive neural networks nodes

The global synchronization problem of complex dynamical networks with memristive neural networks (MNNs) nodes is studied in this paper. By using the Filippov solution and some set-valued maps, the synchronization framework of complex networks with MNNs nodes is presented. Some sufficient criteria ensuring the considered complex networks to be globally exponentially synchronized are derived by using the Kronecker product technique and Lyapunov functional methods. The proposed criteria are given in terms of linear matrix inequalities (LMIs) and only three variables need to be determined. Finally, the effectiveness of the obtained results is illustrated by a numerical example.