Aperiodically intermittent H-infinity synchronization for a class of reaction-diffusion neural networks

作者：Liu, Lijun; Chen, Wu-Hua^*; Lu, Xiaomei

来源：Neurocomputing, 2017, 222: 105-115.

DOI：10.1016/j.neucom.2016.10.020

• Reaction-diffusion neural networks
• Aperiodically intermittent control
• H infinity synchronization
• Switching-time-dependent Lyapunov function
• Linear matrix inequality (LMI)

In this paper, the intermittent H-infinity synchronization problem for a class of reaction-diffusion neural networks with Dirichlet boundary conditions is investigated. Different from the previous works concerning intermittent synchronization, it is assumed that the response system is subject to external disturbance, and both the control period and the control width may be variable. A switching-time-dependent Lyapunov function combined with the use of the extended Wiritinger's inequality for exploring the stabilizing role of the reaction-diffusion term is employed to analyze the exponential stability and L-2-gain performance of the synchronization error dynamics. In the framework of linear matrix inequalities, the aperiodically intermittent H-infinity synchronization controller is designed, which guarantees internally exponential stability as well as a prescribed L-2-gain from the exogenous input to the regulated error output. Two numerical examples are given to illustrate the effectiveness of the proposed method.

• 出版日期2017-1-26
• 单位广西大学