Global exponential stability of cellular neural networks with time-varying discrete and distributed delays

This paper is concerned with the problem of global exponential stability analysis for a class of cellular neural networks with time-varying discrete and distributed delays (DDCNNs). A new delay-dependent sufficient condition is derived for the global exponential stability of the DDCNNs by using the integral inequality method and the newly proposed Lyapunov–Krasovskii functional. The obtained stability condition is less conservative than some of the existing results in the literature. Numerical examples are given to demonstrate the effectiveness and superiority of the proposed results.