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Global Robust Synchronization of Fractional Order Complex Valued Neural Networks with Mixed Time Varying Delays and Impulses

  • Pratap Anbalagan
  • Raja Ramachandran
  • Jinde CaoEmail author
  • Grienggrai Rajchakit
  • Chee Peng Lim
Regular Papers Intelligent Control and Applications
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Abstract

In this article, we explore the theoretical issues on the drive-response synchronization of a class of fractional order uncertain complex valued neural networks (FOUCNNs) with mixed time varying delays and impulses. Based upon the contraction mapping principle, robust analysis techniques, as well as Riemann-Liouville (R-L) derivative, we derive a new set of novel sufficient conditions for the existence and uniqueness of equilibrium point of such neural network system, while by applying the Lyapunov functional approach, the global stability of the equilibrium solutions are obtained. Furthermore, the synchronization criterion of FOUCNNs is also attracted by means of the adaptive error feedback control strategy. Finally, two examples are provided along with the simulation results to demonstrate the effectiveness of our main proofs.

Keywords

Adaptive synchronization asymptotic stability complex valued neural networks Riemann-Liouville derivative 
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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Pratap Anbalagan
    • 1
  • Raja Ramachandran
    • 2
  • Jinde Cao
    • 3
    • 4
    Email author
  • Grienggrai Rajchakit
    • 5
  • Chee Peng Lim
    • 6
  1. 1.Department of MathematicsAlagappa UniversityKaraikudiIndia
  2. 2.Ramanujan Centre for Higher MathematicsAlagappa UniversityKaraikudiIndia
  3. 3.School of MathematicsSoutheast UniversityNanjingChina
  4. 4.School of Mathematics and StatisticsShandong Normal UniversityJi’nanChina
  5. 5.Department of Mathematics, Faculty of ScienceMaejo UniversityChiang MaiThailand
  6. 6.Institute of Intelligent System Research and InnovationDeakin UniversityDeakinAustralia

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