title: Finite-time synchronization control of a class of memristor-based recurrent neural networks.
abstract: This paper presents a global and local finite-time synchronization control law for memristor neural networks. By utilizing the drive-response concept, differential inclusions theory, and Lyapunov functional method, we establish several sufficient conditions for finite-time synchronization between the master and corresponding slave memristor-based neural network with the designed controller. In comparison with the existing results, the proposed stability conditions are new, and the obtained results extend some previous works on conventional recurrent neural networks. Two numerical examples are provided to illustrate the effective of the design method.
authors.affiliation: College of Science, China Three Gorges University, Yichang, Hubei 443002, China. Electronic address: jiangminghui@ctgu.edu.cn.
authors.forename: Minghui
authors.initials: M
authors.lastname: Jiang
authors.affiliation: College of Science, China Three Gorges University, Yichang, Hubei 443002, China. Electronic address: wangshuangtaojy@163.com.
authors.forename: Shuangtao
authors.initials: S
authors.lastname: Wang
authors.affiliation: Centre of New Energy Systems, Department of Electrical and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa. Electronic address: meij0000@163.com.
authors.forename: Jun
authors.initials: J
authors.lastname: Mei
authors.affiliation: College of Science, China Three Gorges University, Yichang, Hubei 443002, China.
authors.forename: Yanjun
authors.initials: Y
authors.lastname: Shen
mesh_terms: D000465:Algorithms; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013995:Time
keywords: Finite-time synchronization; Memristor; Recurrent neural networks