Novel stability criterion for cellular neural networks: An improved Guʹs discretized LKF approach

Novel stability criterion is presented for the existence, uniqueness and globally asymptotic stability of the equilibrium point of a class of cellular neural networks with time-varying delays. Based on Guʹs discretized Lyapunov–Krasovskii functional (LKF) theory, a novel vector LKF is introduced by dividing the variation interval of the time delay into several subintervals with equal length. By using the homeomorphism mapping principle, free-weighting matrix method and linear matrix inequality (LMI) techniques, the obtained condition is less conservative than some previous results. Three examples are also given to show the effectiveness of the presented criterion.