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

Abdujelil Abdurahman; Haijun Jiang; Zhidong Teng

doi:10.1016/j.neunet.2015.04.015

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

Neural Netw. 2015 Sep:69:20-8. doi: 10.1016/j.neunet.2015.04.015. Epub 2015 May 11.

Authors

Abdujelil Abdurahman¹, Haijun Jiang², Zhidong Teng¹

Affiliations

¹ College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, PR China.
² College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, PR China. Electronic address: jianghaijunxju@163.com.

PMID: 26024807
DOI: 10.1016/j.neunet.2015.04.015

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.

Keywords: Finite-time synchronization; Memristor; Neural network; Time-varying delay.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Feedback*
Humans
Neural Networks, Computer*
Nonlinear Dynamics
Time Factors