Boundedness and exponential stability for nonautonomous cellular neural networks with reaction–diffusion terms

Employing Lyapunov functional method, we analyze the ultimate boundedness and global exponential stability of a class of reaction–diffusion cellular neural networks with time-varying delays. Some new criteria are obtained to ensure ultimate boundedness and global exponential stability of delayed reaction–diffusion cellular neural networks (DRCNNs). Without assuming that the activation functions fijl(·) are bounded, the results extend and improve the earlier publications.