Impulsive effects on stability of Cohen–Grossberg-type bidirectional associative memory neural networks with delays

In this paper, the exponential stability is investigated for a class of Cohen–Grossberg-type bidirectional associative memory neural networks with delays and impulsive effects. By using Lyapunov functionals, the analysis method, inequality technique and the properties of an MM-matrix, the delay-independent sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are derived. The obtained results are less restrictive than those given in the earlier literature, and the boundedness and differentiability of the activation functions are removed. An illustrative example is given to demonstrate the effectiveness of the obtained results.