Skip to Main Content
This paper investigates the asymptotical stability for discrete-time Cohen-Grossberg neural networks with both timevarying and distributed delays. By constructing a novel Lyapunov-Krasovskii functional and introducing some free-weighting matrices, one delay-dependent sufficient condition is obtained by using convex combination. The criterion is presented in terms of LMIs and the feasibility can be easily checked with the help of LMI in Matlab Toolbox. In addition, the activation function can be described more generally, which generalizes those earlier methods. Finally, the effectiveness of obtained results can be further illustrated by one numerical example in comparison with the existent ones.