New Results on the Robust Stability of Cohen–Grossberg Neural Networks with Delays

摘要

In this letter, a generalized type of Cohen–Grossberg neural networks with time delays are discussed and their global robust stability of the equilibrium point is investigated. By introducing a set of Lyapunov functionals, several new sufficient conditions guaranteeing the global robust convergence are derived. The results show that the amplification function a i (x) is harmless to the robust stability of Cohen–Grossberg neural networks. Two examples are given to demonstrate the applicability of the proposed results.