Novel approach to cluster synchronization of delayed neural networks

Cluster synchronization of delayed neural networks with randomly formed clusters is investigated. In this paper, a distributed approach is proposed to make a delayed neural network achieve cluster synchronization. Furthermore, the coupling strength between nodes adopts locally adaptive strategy, which is only based on its local information. A sufficient condition about the global stability of cluster synchronization of delayed neural networks is derived. Numerical simulations show the effectiveness of the strategy.