Stability of nonlinear time-delay systems with parameter uncertainties with an application to neural networks

First considers a family of nonlinear time-delay systems with uncertainties and establishes sufficient conditions for the asymptotic stability of an equilibrium for this family. The authors then apply these results to the stability analysis of a class of artificial neural networks with transmission delays. These results require the verification of the definiteness of a certain matrix or the verification of a certain inequality. The authors´ results provide also a method of estimating the domain of attraction of an asymptotically stable equilibrium of the time-delay neural networks