Finite-time H∞ boundedness of discrete-time neural networks normbounded disturbances with time-varying delay

The problem of finite-time H∞ performance of discrete time neural network with norm-bounded disturbances and time varying delays is studied in this paper. By constructing a delay-dependent Lyapunov-Krasovskii functional and using a two-term approximation of the time-varying delay, sufficient conditions of finite-time stability are derived and expressed in terms of linear matrix inequalities (LMIs). The derived stability conditions can be applied into analyzing the finite-time stability and deriving the maximally tolerable delay. Comparision with the existing results given to show that, the derived stability conditions are less conservative. Finally, numerical examples are provided to illustrate the effectiveness of the proposed method.