On global exponential stability of cellular neural networks with Lipschitz-continuous activation function and variable delays

摘要

For a class of cellular neural networks (CNNs) with variable delays, this paper presents some new sufficient conditions for guaranteeing the global exponential stability. These conditions are derived by using Lyapunov functional method and combining with the inequality 3abc⩽a3+b3+c3 (a,b,c>0) technique. Furthermore, these stability conditions depend only on the network's coefficients, and are totally independent of the delays. The results, which do not require the cloning template to be symmetric, are easy to use in network design. Compared with existing results, our results are shown to be superior to other ones. Numerical examples are given to demonstrate the effectiveness of our results.