Stability and Existence of Periodic Solutions of Periodic Cellular Neural Networks with Time-Vary Delays

By using the continuation theorem of Mawhins coincidence degree theory and constructing a suitable Lyapunov function, some new sufficient conditions are obtained ensuring existence and global asymptotical stability of periodic solution of cellular neural networks with periodic coefficients and delays, which do not require the activation functions to be differentiable and monotone nondecreasing. A numerical example is given to illustrate that the criteria are feasible. These results are helpful to design globally asymptotically stable and periodic oscillatory cellular neural networks.