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

• The paper presents new results on global stability of second-order interval CGNNs.
• It is the first paper to study global stability of general second-order interval CGNNs.
• The new results can also be used to verify the stability of first-order interval CGNNs.

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.