New conditions for global exponential stability of cellular neural networks with delays

In this paper, we study further a class of cellular neural networks model with delays. By employing the inequality a∏k=1mbkqk≤1r∑k=1mqkbkr+1rar(a≥0,bk≥0,qk>0with∑k=1mqk=r−1,andr>1), constructing a new Lyapunov functional, and applying the Homeomorphism theory, we derive some new conditions ensuring the existence, uniqueness of the equilibrium point and its global exponential stability for cellular neural networks. These conditions are independent of delays and posses infinitely adjustable real parameters, which are of highly important significance in the designs and applications of networks. In addition, we extend or improve the previously known results.