Global exponential stability of a class of neural networks with variable delays

In this paper, the conditions ensuring existence, uniqueness, and global exponential stability of the equilibrium point of a class of neural networks with variable delays are studied. Without assuming global Lipschitz conditions on these activation functions, applying idea of vector Lyapunov function, the sufficient conditions for global exponential stability of neural networks are obtained.