An improved stability criterion of neural networks with time-varying delays in the form of quadratic function using novel geometry-based conditions

Tae H. Lee, Myeong Jin Park and Ju H. Park

Applied Mathematics and Computation, 2021, vol. 404, issue C

Abstract: In this paper, the stability problem of neural networks is addressed by considering time-varying delays. By proposing novel geometry-based negative conditions for the form of quadratic function and constructing new augmented Lyapunov-Krasovskii functionals, a novel stability criterion is derived. Finally, to show the effectiveness of the proposed criterion, several numerical examples are given.

Keywords: Neural networks; Time-varying delay; Stability; Quadratic function (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:404:y:2021:i:c:s0096300321003167

DOI: 10.1016/j.amc.2021.126226

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