Novel pinning control strategy for coupled neural networks with communication column graphs

This paper deals with the problem of chaotic synchronization for coupled neural networks by a novel control strategy. Additional communication control graphs which prescribe the information flow available for controls purposes are introduced, and such pinning system has not been investigated before. Many relaxed information are used to construct augmented Lyapunov-Krasovskii functional (LKF), which makes use of more relax variables by employing the new type augmented matrices with Kronecker produce operation. By resorting to Lyapunov function methods and analysis techniques, the tasks to get the pinning synchronization of dynamical networks are solved in terms of a set of LMI inequalities, which are easy to be analyzed or tested. Finally, numerical simulations are performed to demonstrate the effectiveness of the analytical results.