title: Finite-time synchronization for memristor-based neural networks with time-varying delays.
abstract: Memristive network exhibits state-dependent switching behaviors due to the physical properties of memristor, which is an ideal tool to mimic the functionalities of the human brain. In this paper, finite-time synchronization is considered for a class of memristor-based neural networks with time-varying delays. Based on the theory of differential equations with discontinuous right-hand side, several new sufficient conditions ensuring the finite-time synchronization of memristor-based chaotic neural networks are obtained by using analysis technique, finite time stability theorem and adding a suitable feedback controller. Besides, the upper bounds of the settling time of synchronization are estimated. Finally, a numerical example is given to show the effectiveness and feasibility of the obtained results.
authors.affiliation: College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, PR China.
authors.forename: Abdujelil
authors.initials: A
authors.lastname: Abdurahman
authors.affiliation: College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, PR China. Electronic address: jianghaijunxju@163.com.
authors.forename: Haijun
authors.initials: H
authors.lastname: Jiang
authors.affiliation: College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, PR China.
authors.forename: Zhidong
authors.initials: Z
authors.lastname: Teng
mesh_terms: D000465:Algorithms; D005246:Feedback; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors
keywords: Finite-time synchronization; Memristor; Neural network; Time-varying delay