Abstract: The existence of equilibrium and global stability are analyzed for delayed Hopfield neural network models, which have no the original requirements for monotonicity and differentiability in the activation function. By using M matrix theory, Liapunov functionals are constructed to establish the sufficient conditions for global asymptotic stability, thus the existing relevant results are improved.