Finite-time synchronization for memristor-based neural networks with time-varying delays. (September 2015)

• Record Type: Journal Article
• Authors: Abdurahman, Abdujelil; Jiang, Haijun; Teng, Zhidong
• Is Part Of: Neural networks. Volume 69(2015:Sep.)
• Page Start: 20
• Page End: 28
• Publication Date: 2015-09
• Subjects: Memristor -- Finite-time synchronization -- Neural network -- Time-varying delay; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2015.04.015
• Languages: English
• ISSNs: 0893-6080

Abstract

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.