Synchronization of Memristor-Based Time-Delayed Neural Networks via Pinning Control

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10636)


As the realization of memristor by HP Lab, more and more researchers pay attention to the memristor-based neural networks (MNNs). In this paper, a pinning control method is applied to drive two MNNs to achieve synchronization. Conditions about the pinning controllers are given to guarantee the asymptotic synchronization of MNNs with time-varying delays. Furthermore, MNNs are nonlinear state-dependent systems with discontinuous right-hand sides such that all the dynamic analyses are under the framework of Filippov’s solutions and the theory of differential inclusions. The effectiveness of the proposed pinning method is verified by a numerical example.


Memristor-based neural networks Asymptotic synchronization Pinning control Time-delay 



This work was supported in part by the National Natural Science Foundation of China under Grants 61233001, 61273140, 61304086, 61374105, 61503377, 61533017, 61473011 and U1501251.


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijingChina
  2. 2.The State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation, Chinese Academy of SciencesBeijingChina
  3. 3.School of AutomationGuangdong University of TechnologyGuangzhouChina

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