Convergence analysis for second-order interval Cohen–Grossberg neural networks

This paper presents new theoretical results on global stability of a class of second-order interval Cohen–Grossberg neural networks. The new criteria is derived to ensure the existence, uniqueness and global stability of the equilibrium point of neural networks under uncertainties. And we make some comparisons between our results with the existed corresponding results. Some examples are provided to show the effectiveness of the obtained results.