Global Uniform Asymptotic Stability of Cellular Neural Networks with Mutli-Porportional Delays

A class of cellular neural networks with multi-proportional delays is studied in this paper. The transformation zi(t)=yi(et) transforms cellular neural networks with multi-proportional delays into cellular neural networks with variable coefficient and constant delays, and then constructing Lyapunov functionals, some delay-independent sufficient conditions are given. These new sufficient conditions can ensure global uniform asymptotic stability of this system. An example is given to illustrate the correctness of obtained results.