Improved Robust Stability Criteria for Delayed Cellular Neural Networks via the LMI Approach

Uniqueness and robust exponential stability are analyzed for a class of uncertain cellular neural networks with time-varying delays. By dividing the variation interval of the time delay into two subintervals with equal length, a novel Lyapunov-Krasovskii functional is introduced. Using the free-weighting matrix method, a new delay-dependent stability criterion is obtained, which is less conservative than some previous literature. Since the result is presented in terms of linear matrix inequalities, the condition is easy to be verified. Finally, an example is given to illustrate the effectiveness of our proposed method.