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The European Physical Journal Special Topics

, Volume 228, Issue 10, pp 2111–2122 | Cite as

Novel criteria of ISS analysis for delayed memristive BAM neural networks

  • Yong ZhaoEmail author
  • Shanshan Ren
  • Jürgen Kurths
Regular Article
  • 11 Downloads
Part of the following topical collections:
  1. Memristor-based Systems: Nonlinearity, Dynamics and Applications

Abstract

In this paper, a class of delayed memristive bidirectional associative memory (BAM) are discussed. Based on system theory and nonsmooth analysis, some novel conditions are obtained to ensure the input-to-state stability (ISS) of such neural networks. Finally, an example is presented to illustrate the feasibility of our results.

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Copyright information

© EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mathematics and Information Science, Henan Polytechnical UniversityJiaozuoP.R. China
  2. 2.Institute of Physics, Humboldt UniversityBerlinGermany
  3. 3.Potsdam Institute for Climate Impact ResearchPotsdamGermany

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