Novel delay-dependent criteria for global robust exponential stability of delayed cellular neural networks with norm-bounded uncertainties ?
The problem ensuring the global robust exponential stability of a class of delayed cellular neural networks with norm-bounded uncertainties is studied. Without assuming the boundedness of the activation functions, by applying the idea of vector Lyapunov function and linear matrix inequality (LMI) techniques, some sufficient conditions for the global robust exponential stability of uncertain cellular neural networks and the existence, uniqueness, global exponential stability of cellular neural networks are obtained, which generalize the previous results in the literature. The criteria are easy to be verified, since they take the form of LMI. Three illustrative examples are given to demonstrate the effectiveness of the proposed results.
linear matrix inequality uncertain cellular neural networks global exponential stability (ges) global robust exponential stability (gres) time-varying delays