Global asymptotic stability of delayed Cohen–Grossberg neural networks

Abstract In this letter, the global asymptotic stability of a class of Cohen–Grossberg neural networks with time-varying delays is discussed. A new set of sufficient conditions for the neural networks are proposed to guarantee the global asymptotic convergence. Our criteria represent an extension of the existing results in literatures. An example is also presented to compare our results with the previous results.