Global exponential stability in neural network with delays

This paper studies the problem of global exponential stability of the equilibrium of a class of neural networks with delays, by using the method of variation of constants and combining it with the method of inequality analysis. Sufficient conditions for global exponential stability of neural networks with delays are obtained, for which we do not require symmetry of the connection matrix and nonlinear properties for neural units to be continuously differentiable or strictly monotonically increasing. These conditions can be used to design globally stable neural networks.