Global robust exponential stability for second-order Cohen–Grossberg neural networks with multiple delays

In this paper, we first discuss the existence and uniqueness of an equilibrium point of a general second-order Cohen–Grossberg neural networks with multiple neurons by means of using fixed point theory. Then by applying the existence result of an equilibrium point and constructing a Lyapunov functional candidate, we study the global robust exponential stability of equilibrium solution to the neural networks. In the last section, we also give an example to demonstrate the validity of our global robust exponential stability result for above neural network.