Global exponential robust stability of Cohen–Grossberg neural network with time-varying delays and reaction–diffusion terms

In this paper, the global exponential robust stability is investigated for Cohen–Grossberg neural network with time-varying delays and reaction–diffusion terms, this neural network contains time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. Neither the boundedness and differentiability on the activation functions nor the differentiability on the time-varying delays are assumed. By using general Halanay inequality and M-matrix theory, several new sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential robust stability of equilibrium point for Cohen–Grossberg neural network with time-varying delays and reaction–diffusion terms. Several previous results are improved and generalized, and three examples are given to show the effectiveness of the obtained results.