Absolutely exponential stability in delayed cellular neural networks

In this paper, without assuming the boundedness, monotonicity and differentiability of the activation functions, we present a necessary and sufficient condition ensuring the existence and uniqueness of the equilibrium point of cellular neural network with fixed time delays (DCNNs). Using M‐matrix theory, Liapunov functionals and functions are constructed and employed to establish sufficient conditions for absolutely exponential stability of DCNNs. The results are applicable to DCNNs with both symmetric and non‐symmetric interconnection matrices, and globally Lipschitz continuous activation functions.