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Finite-time synchronization for memristor-based neural networks with time-varying delays.

Authors :
Abdurahman, Abdujelil
Jiang, Haijun
Teng, Zhidong
Source :
Neural Networks. Sep2015, Vol. 69, p20-28. 9p.
Publication Year :
2015

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08936080
Volume :
69
Database :
Academic Search Index
Journal :
Neural Networks
Publication Type :
Academic Journal
Accession number :
108362859
Full Text :
https://doi.org/10.1016/j.neunet.2015.04.015