Neural Networks2022，Vol.14610.DOI:10.1016/j.neunet.2021.11.007

Stability and dissipativity criteria for neural networks with time-varying delays via an augmented zero equality approach

Lee S.H. Park M.J. Ji D.H. Kwon O.M.
Neural Networks2022，Vol.14610.DOI:10.1016/j.neunet.2021.11.007
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  • NSTL
  • Elsevier

Stability and dissipativity criteria for neural networks with time-varying delays via an augmented zero equality approach

Lee S.H. 1Park M.J. 2Ji D.H. 3Kwon O.M.1
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作者信息

  • 1. School of Electrical Engineering Chungbuk National University
  • 2. Center for Global Converging Humanities Kyung Hee University
  • 3. Samsung Advanced Institute Of Technology Samsung Electronics
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Abstract

? 2021 Elsevier LtdThis work investigates the stability and dissipativity problems for neural networks with time-varying delay. By the construction of new augmented Lyapunov–Krasovskii functionals based on integral inequality and the use of zero equality approach, three improved results are proposed in the forms of linear matrix inequalities. And, based on the stability results, the dissipativity analysis for NNs with time-varying delays was investigated. Through some numerical examples, the superiority and effectiveness of the proposed results are shown by comparing the existing works.

Key words

Dissipativity analysis/Lyapunov method/Neural Network/Stability/Time-varying delay

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出版年

2022
Neural Networks

Neural Networks

EISCI
ISSN：0893-6080
被引量16
参考文献量53
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