State estimation and input-to-state stability of impulsive stochastic BAM neural networks with mixed delays

This paper concerns with dynamical behaviors for a class of impulsive BAM neural networks with stochastic effects and mixed delays. By establishing integral-differential inequalities with time-varying inputs, we give the pth moment state estimation and obtain some sufficient conditions ensuring pth asymptotical input-to-state stability and pth exponential input-to-state stability with variable gains for the impulsive stochastic neural networks with delays. The present approach can remove some conservative and restrictive conditions on input-to-state stability given in existing publications and extend to more general stochastic delayed systems with nonlinear impulses.