LAUSR

Abstract This paper concentrates on the passive synchronization issue for Markov jump neural networks subject to randomly occurring gain variations, in which the event-triggered mechanism is employed to save the limited communication resource. Moreover, the gain variations of the controller are considered to occur in a random way, which is modeled by a Bernoulli parameter. The goal is to build a controller which ensures that the synchronization error system is stochastically stable and satisfies a passive property. By utilizing the stochastic analysis theory and convex optimization technique, some results with less conservatism are derived. Ultimately, the effectiveness and validity of the design method are illustrated by a numerical example.