Event-triggered non-fragile state estimation for delayed neural networks with randomly occurring sensor nonlinearity

This paper is concerned with event-triggered non-fragile state estimator design for delayed neural networks subject to randomly occurring sensor nonlinearity. Different from the existing event-triggered scheme, a new event-triggered scheme is designed which is dependent on the incomplete measurement. The adopted event-triggered scheme is introduced between the neural networks and state estimator for the purpose of energy saving. Considering the sensor nonlinearity and using the event-triggered scheme, a new estimation error system is modeled. Based on this model, a sufficient condition is derived to guarantee the asymptotical stability of estimation error system. Furthermore, a desired event-triggered non-fragile estimator is designed by solving a set of linear matrix inequalities. Finally, a numerical example is provided to illustrate the usefulness of the proposed method.