Synchronization of coupled reaction-diffusion neural networks with switching topology via generalized intermittent control and adaptive strategy

The synchronization problem of linearly coupled reaction-diffusion neural networks with switching topology is discussed in this paper. At first, a generalized intermittent control and its adaptive strategy are introduced. This type of control strategy can unify the traditional periodic intermittent control and the aperiodic case, and the adaptive control gains depend on space as well as time. Moreover, based on the designed control protocol, some novel and readily verified criteria, which have a close relationship with the diffusion coefficients and coupled strengths, are established to guarantee the synchronization of the considered networks. Finally, the effectiveness of the proposed control strategy is shown by a numerical example.