Pinning synchronization of memristor-based neural networks with time-varying delays

Zhanyu Yang; Biao Luo; Derong Liu; Yueheng Li

doi:10.1016/j.neunet.2017.05.003

Pinning synchronization of memristor-based neural networks with time-varying delays

Neural Netw. 2017 Sep:93:143-151. doi: 10.1016/j.neunet.2017.05.003. Epub 2017 May 18.

Authors

Zhanyu Yang¹, Biao Luo², Derong Liu³, Yueheng Li⁴

Affiliations

¹ The School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China. Electronic address: yangzhanyu@hotmail.com.
² The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. Electronic address: biao.luo@hotmail.com.
³ The School of Automation, Guangdong University of Technology, Guangzhou 510006, China. Electronic address: derongliu@foxmail.com.
⁴ The School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China. Electronic address: yuehengli@hotmail.com.

PMID: 28582671
DOI: 10.1016/j.neunet.2017.05.003

Abstract

In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and response system, respectively. The dynamics are studied by theories of differential inclusions and nonsmooth analysis. In addition, some sufficient conditions are derived to guarantee asymptotic synchronization and exponential synchronization of memristor-based neural networks via the presented pinning control. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, the effectiveness of the obtained results is demonstrated by numerical simulations.

Keywords: Asymptotic synchronization; Exponential synchronization; Memristor-based neural networks; Pinning control; Time-varying delays.

MeSH terms

Electronics / methods
Neural Networks, Computer*
Selection Bias
Time Factors