Anti-synchronization Control of Memristive Neural Networks with Multiple Proportional Delays
详细信息    查看全文
  • 作者:Weiping Wang ; Lixiang Li ; Haipeng Peng ; Jürgen Kurths…
  • 关键词:Memristive neural networks ; Proportional delay ; Anti ; synchronization
  • 刊名:Neural Processing Letters
  • 出版年:2016
  • 出版时间:February 2016
  • 年:2016
  • 卷:43
  • 期:1
  • 页码:269-283
  • 全文大小:532 KB
  • 参考文献:1.Pershin Y, DiVentra M (2010) Experimental demonstration of associative memory with memristive neural networks. Neural Netw 23:881–886CrossRef
    2.Hu X, Wang J (2010) Global uniform asymptotic stability of memristor-based recurrent neural networks with time delays. International Joint Conference on Neural Networks (IJCNN 10), Barcelona, pp 1–8
    3.Wu A, Zeng Z, Zhu X, Zhang J (2011) Exponential synchronization of memristor-based recurrent neural networks with time delays. Neurocomputing 74:3043–3050CrossRef
    4.Wu A, Wen S, Zeng Z (2012) Synchronization control of a class of memristor-based recurrent neural networks. Inf Sci 183:106–116MathSciNet CrossRef
    5.Wu A, Zhang J, Zeng Z (2011) Dynamic behaviors of a class of memristor-based Hopfield networks. Phys Lett A 375:1661–1665MathSciNet CrossRef
    6.Wen S, Zeng Z (2012) Dynamics analysis of a class of memristor-based recurrent networks with time-varying delays in the presence of strong external stimuli. Neural Process Lett 35:47–59CrossRef
    7.Wang W, Li L, Peng H, Xiao J, Yang Y (2014) Synchronization control of memristor-based recurrent neural networks with perturbations. Neural Netw 53:8–14CrossRef
    8.Ren F, Cao J (2009) Anti-synchronization of stochastic perturbed delayed chaotic neural networks. Neural Comput Appl 18:515–521CrossRef
    9.Song Q, Cao J (2007) Synchronization and anti-synchronization for chaotic systems. Chaos Solitons Fractals 33(3):929–939MathSciNet CrossRef
    10.Wu A, Zeng Z (2013) Anti-synchronization control of a class of memristive recurrent neural networks. Commun Nonlinear Sci Numer Simul 18:373–385MathSciNet CrossRef
    11.Chandrasekar A, Rakkiyappan R, Cao J, Lokshmanan S (2014) Synchronization of memristor-based recurrent neural networks with two delay components based on second-order reciprocally approach. Neural Netw 57:79–93CrossRef
    12.Yang X, Cao J, Yu W (2014) Exponential synchronization of memristive Cohen-Grossberg neural networks with mixed delays. Cogn Neurodyn 8:239–249CrossRef
    13.Liu Y (1996) Asymptotic behavior of functional differential equations with proportional time delays. Eur J Appl Math 7(1):11–30CrossRef
    14.Van B, Marshall J, Wake G (2004) Holomorphic solutions to pantograph type equations with neural fixed points. J Math Anal Appl 295(2):557–569MathSciNet CrossRef
    15.Zhou L (2011) On the global dissipativity of a class of cellular neural networks with multipantograph delays. Adv Artif Neural Syst 941426
    16.Zhou L (2013) Dissipativity of a class of cellular neural networks with proportional delays. Nonlinear Dyn 73:1895–1903CrossRef
    17.Zhou L (2013) Delay-dependent exponential stability of cellular neural networks with multi-proportional delays. Neural Process Lett 38:347–359CrossRef
    18.Zheng C, Li N, Cao J (2015) Matrix measure based stability criteria for high-order neural networks with proportional delay. Neurocomputing 149:1149–1154CrossRef
    19.Wu A, Zeng Z (2014) New global exponential stability results for a memristive neural systems with time-varying delays. Neurocomputing 144:553–559CrossRef
    20.Filippov A (1988) Differential equations with discontinuous right-hand sides. Kluwer, DordrechtCrossRef
    21.Wu H, Zhang L (2013) Almost periodic solution for memristive neural networks with time-varying delays. J Appl Math 2013(716172):12
  • 作者单位:Weiping Wang (1)
    Lixiang Li (2)
    Haipeng Peng (2)
    Jürgen Kurths (3)
    Jinghua Xiao (1)
    Yixian Yang (2) (4)

    1. School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China
    2. Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China
    3. Potsdam Institute for Climate Impact Research, 14473, Potsdam, Germany
    4. National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  • 刊物类别:Physics and Astronomy
  • 刊物主题:Physics
    Complexity
    Artificial Intelligence and Robotics
    Electronic and Computer Engineering
    Operation Research and Decision Theory
  • 出版者:Springer Netherlands
  • ISSN:1573-773X
文摘
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. Keywords Memristive neural networks Proportional delay Anti-synchronization

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700