This paper examines a passivity analysis for a class of discrete-time recurrent neural networks DRNNs with norm-bounded time-varying parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate type of Lyapunov functional, sufficient passivity conditions for the DRNNs are derived in terms of a family of linear matrix inequalities LMIs . Two numerical examples are given to illustrate the effectiveness and applicability.
