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Global dissipativity of high-order Hopfield bidirectional associative memory neural networks with mixed delays

  • Chaouki AouitiEmail author
  • Rathinasamy Sakthivel
  • Farid Touati
Original Article
  • 16 Downloads

Abstract

In this paper, the problem of the global dissipativity of high-order Hopfield bidirectional associative memory neural networks with time-varying coefficients and distributed delays is discussed. By using Lyapunov–Krasovskii functional method, inequality techniques and linear matrix inequalities, a novel set of sufficient conditions for global dissipativity and global exponential dissipativity for the addressed system is developed. Further, the estimations of the positive invariant set, globally attractive set and globally exponentially attractive set are found. Finally, two examples with numerical simulations are provided to support the feasibility of the theoretical findings.

Keywords

BAM high-order neural networks Global dissipativity Global exponential dissipativity Time-varying delay Distributed delays 

Notes

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Sciences of Bizerta, Department of Mathematics, Research Units of Mathematics and Applications UR13ES47University of CarthageZarzounaTunisia
  2. 2.Department of Applied MathematicsBharathiar UniversityCoimbatoreIndia
  3. 3.Department of MathematicsSungkyunkwan UniversitySuwonSouth Korea

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