Stability for a retarded impulsive Cohen–Grossberg BAM neural network system

Sakina Othmani*, Nasser eddine Tatar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, an impulsive Cohen-Grossberg bidirectional associative neural network with both time-varying and distributed delays is examined. Novel sufficient conditions for deriving stability with a desired rate, including the exponential one, are obtained. We consider a large class of admissible kernels encompassing the existing ones. Our findings cover the existing stability results in the literature. Finally, a numerical example is given for the validation of the theoretical outcomes.

Original languageEnglish
Pages (from-to)709-728
Number of pages20
JournalJournal of Experimental and Theoretical Artificial Intelligence
Volume35
Issue number5
DOIs
StatePublished - 2023

Bibliographical note

Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Cohen-Grossberg
  • General stability
  • bidirectional associative memory
  • distributed delay
  • impulse
  • time-varying delay

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence

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