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

This 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 li...

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Bibliographic Details
Published in:Neural networks 2022-02, Vol.146, p.141-150
Main Authors: Lee, S.H., Park, M.J., Ji, D.H., Kwon, O.M.
Format: Article
Language:English
Subjects:
Algorithms
Dissipativity analysis
Lyapunov method
Neural Network
Neural Networks, Computer
Stability
Time-varying delay
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Summary:This 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.
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2021.11.007