English, Article edition: DELAY-DEPENDENT GLOBAL ROBUST ASYMPTOTIC STABILITY ANALYSIS OF BAM NEURAL NETWORKS WITH TIME DELAY: AN LMI APPROACH XU-YANG LOU; BAO-TONG CUI

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Bookmark: http://trove.nla.gov.au/version/133006
Physical Description
  • article
Language
  • English

Edition details

Title
  • DELAY-DEPENDENT GLOBAL ROBUST ASYMPTOTIC STABILITY ANALYSIS OF BAM NEURAL NETWORKS WITH TIME DELAY: AN LMI APPROACH
Author
  • XU-YANG LOU
  • BAO-TONG CUI
Physical Description
  • article
Notes
  • The global robust asymptotic stability of bi-directional associative memory (BAM) neural networks with constant or time-varying delays is studied. An approach combining the Lyapunov-Krasovskii functional with the linear matrix inequality (LMI) is taken to study the problem. Some a criteria for the global robust asymptotic stability, which gives information on the delay-dependent property, are derived. Some illustrative examples are given to demonstrate the effectiveness of the obtained results.
  • Bi-directional associative memory neural networks, delay, robust asymptotic stability, linear matrix inequality, Lyapunov-Krasovskii functional
  • RePEc:wsi:nmncxx:v:03:y:2007:i:01:p:57-68
Language
  • English
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