Mean-square asymptotical synchronization control and robust analysis of discrete-time neural networks with time-varying delay. (2nd October 2018)

• Record Type: Journal Article
• Authors: Lin, De-hui; Wu, Jun; Zhu, Yang; Cai, Jian-ping; Li, Jian-ning
• Is Part Of: Automatika. Volume 59:Number 3/4(2018)
• Page Start: 382
• Page End: 390
• Publication Date: 2018-10-02
• Subjects: Asymptotical synchronization control -- discrete-time neural networks -- time-varying delay -- controller nonlinearity -- uncertainty; Automatic control -- Periodicals; 629.805
• DOI: 10.1080/00051144.2018.1552651
• Languages: English
• ISSNs: 0005-1144

Abstract

ABSTRACT: This paper investigates the controller design problem for mean-square asymptotical synchronization of discrete-time neural networks with time-varying delay. We proposed the design method of synchronization controller, which considered the nonlinearity of controller input. Based on the designed controller, a delay-dependent synchronization criterion is proposed and formulated in the form of linear matrix inequalities (LMIs) by applying the Lyapunov function method. The result is extended to the delayed discrete-time neural network with uncertainty. Two numerical examples are presented to illustrate the effectiveness of the proposed method.