Extended dissipativity stabilization and synchronization of uncertain stochastic reaction-diffusion neural networks via intermittent non-fragile control

摘要

This paper mainly studies the problem of extended dissipativity stabilization and synchronization of a class of uncertain stochastic reaction-diffusion neural networks with discrete and distributed time-varying delays via intermittent non-fragile control strategies. A novel stabilization and synchronization criteria and extended dissipative analysis is obtained by combining a switching time dependent Lyapunov functional method with Wirtinger's inequality technique. Then, by solving a set of delay dependent linear matrix inequalities, we obtain the desired intermittent non-fragile controller, which can be used to satisfies the prescribed level of extended dissipativity behaviors, including H-infinity behavior, passivity action, (Q, S, R)-dissipative performance, and L-2 - L-infinity performance. Finally, two numerical examples are adopted to verify the validity of the stabilization and synchronization results. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.