Neural Processing Letters

, Volume 43, Issue 1, pp 269–283 | Cite as

Anti-synchronization Control of Memristive Neural Networks with Multiple Proportional Delays

  • Weiping Wang
  • Lixiang LiEmail author
  • Haipeng Peng
  • Jürgen Kurths
  • Jinghua Xiao
  • Yixian Yang


This paper investigates anti-synchronization control of memristive neural networks with multiple proportional delays. Here, we first study the proportional delay, which is a kind of unbounded time-varying delay in the memristive neural networks, by using the differential inclusion theory to handle the memristive neural networks with discontinuous right-hand side. In particular, several new criteria ensuring anti-synchronization of memristive neural networks with multiple proportional delays are presented. In addition, the new proposed criteria are easy to verify and less conservative than earlier publications about anti-synchronization control of memristive neural networks. Finally, two numerical examples are given to show the effectiveness of our results.


Memristive neural networks Proportional delay Anti-synchronization 



This paper is supported by the National Natural Science Foundation of China (Grant Nos. 61170269, 61472045), the Beijing Higher Education Young Elite Teacher Project (Grant No. YETP0449), the Asia Foresight Program under NSFC Grant (Grant No. 61411146001) and the Beijing Natural Science Foundation (Grant No. 4142016).


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Weiping Wang
    • 1
  • Lixiang Li
    • 2
    Email author
  • Haipeng Peng
    • 2
  • Jürgen Kurths
    • 3
  • Jinghua Xiao
    • 1
  • Yixian Yang
    • 2
    • 4
  1. 1.School of ScienceBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Information Security Center, State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingChina
  3. 3.Potsdam Institute for Climate Impact ResearchPotsdamGermany
  4. 4.National Engineering Laboratory for Disaster Backup and RecoveryBeijing University of Posts and TelecommunicationsBeijingChina

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