Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism

This paper is concerned with the nonfragile state estimation for a kind of delayed fractional-order neural network under event-triggered mechanism (ETM). To reduce bandwidth occupation communication network, ETM employed in sensor-to-estimator channel. Moreover, order to reflect reality, transmission delay taken into account model establishment. Sufficient criteria are supplied make sure that augmented system asymptotically stable by using Lyapunov indirect approach and linear matrix inequality method. In end, theoretical result shown means two numerical examples.