Robust passivity analysis of a class of discrete-time stochastic neural networks
This paper addresses the passivity problem of a class of discrete-time stochastic neural networks with time-varying delays and norm-bounded parameter uncertainties. New delay-dependent passivity conditions are obtained by using a novel Lyapunov functional together with the linear matrix inequality approach. Numerical examples show the effectiveness of the proposed method.
passivity discrete-time stochastic neural networks linear matrix inequality