New robust passivity criteria for stochastic fuzzy BAM neural networks with time-varying delays

In this paper, we consider the problem of passivity analysis issue for a class of stochastic fuzzy BAM neural networks with time varying delays. By employing the idea of delay-fractioning technique and Lyapunov stability theory, a new set of sufficient conditions are derived in terms of linear matrix inequalities for obtaining the passivity condition of the considered neural network model. First, we derive the passivity condition for stochastic fuzzy BAM neural networks with time varying delays and then the result is extended to the case with uncertainties. Two numerical examples are given to illustrate the effectiveness and conservatism of the obtained results.

► The problem of passivity analysis issue for stochastic fuzzy BAM neural networks with delays has been considered.
► By applying a delay-fractioning technique, a new set of conditions are established in terms of LMI inequalities.
► Numerical examples are given to illustrate the effectiveness and less conservativeness of our obtained theory.