Robust Exponential Stability Analysis for Interval Neural Networks with Time Delay

The problem of robust exponential stability analysis for nonlinear uncertain interval neural networks with time delay is investigated. The nonlinear uncertainties are assumed to satisfy the cone constraint conditions. The interval parameters of the neural networks are equivalent to norm matched parameter uncertainties via some matrix transformations. The stable criteria for the uncertain interval neural networks with time delays are developed by use of the Lyapunov stability theory. All the stability conditions in this paper are presented in terms of linear matrix inequalities.