Anti-synchronization control for delayed memristor-based distributed parameter NNs with mixed boundary conditions

Advances in Difference Equations

Weiyuan Zhang¹  Junmin Li²  Chenyang Ding³ 

[1] Institute of Nonlinear Science, Xianyang Normal University, Xianyang, P.R. China;School of Mathematics and Statistics, Xidian University, Xi’an, P.R. China

关键词: memristor;    distributed parameter neural networks;    intermittent sampled-data control;    anti-synchronization;   

DOI  :  10.1186/s13662-016-1017-x

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

This paper addresses the anti-synchronization control problem of memristor-based distributed parameter neural networks (MDPNNs) with time-varying delays. An intermittent sampled-data controller is proposed such that the response system can be anti-synchronized with the drive system by using Lyapunov stability theory. The design approach of the desired intermittent sampled-data controller is first proposed. Based on a differential inequality and linear matrix inequality (LMI) technology, novel sufficient conditions for the exponential anti-synchronization are obtained in terms of line matrix inequalities. Numerical simulations are shown to demonstrate the effectiveness of the theoretical results.

【 授权许可】

CC BY