Mean-square asymptotical synchronization control and robust analysis of discrete-time neural networks with time-varying delay

• Main Authors: Lin, De-hui, Wu, Jun, Zhu, Yang, Cai, Jian-ping, Li, Jian-ning
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2019
• Subjects: Engineering::Civil engineering; Asymptotical Synchronization Control; Discrete-time Neural Networks
• Online Access: https://hdl.handle.net/10356/104631; http://hdl.handle.net/10220/49518
• Institution: Nanyang Technological University

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.