Sampled-data-based exponential synchronization of switched coupled neural networks with unbounded delay

Abstract

Based on sampled-data control, the exponential synchronization problem for a class of switched coupled neural networks with mixed delays is studied in the article. Considering the phenomena of mismatch between the controller and system, asynchronous switching occurs when switching signals appear in the sampling interval. Different from the existing results, the switched neural networks are based on coupling information. Then, an improved bilateral Lyapunov–Krasovskii functional is constructed, which involves more information. By using Bessel–Legendre inequality, some sufficient conditions for the exponential stability of synchronization error system are obtained by linear matrix inequalities. Average dwell time is obtained in the form of inequality that includes the maximum inter-event interval. Finally, two examples are used to illustrate the validity and feasibility of the proposed method.