Convergence for a class of delayed recurrent neural networks without M-matrix condition

In this paper, we investigate the asymptotic behavior of solutions to a class of recurrent neural network model with delays. Without assuming MM-matrix condition, it is shown that every solution of the network tends to an equilibrium point as t→∞t→∞. Our results improve and extend some corresponding ones already known.