Improved stability criteria for the neural networks with time-varying delay via new augmented Lyapunov–Krasovskii functional

Zhen-Man Gao, Yong He and Min Wu

Applied Mathematics and Computation, 2019, vol. 349, issue C, 258-269

Abstract: The stability issue of neural networks with time-varying delay is investigated in this paper. Firstly, a kind of new augmented single integral which involves s-dependent integral terms (∫stx(θ)dθ and ∫st−d(t)x(θ)dθ) is proposed. Then, to further reduce the conservatism of stability criteria, one less-conservative LKF augmented integral terms (∫t−d(t)tx(θ)dθ,∫t−ht−d(t)x(θ)dθ,∫t−d(t)t∫stx(θ)d(t)dθds and ∫t−ht−d(t)∫st−d(t)x(θ)d(t)dθds) is employed, which considering more interrelation system states is employed. Finally, two numerical examples are employed to illustrate the effectiveness of proposed methods and the results verify the feasibility.

Keywords: Neural networks; Time-varying delay; Stability analysis; Lyapunov–Krasovskii functional (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:349:y:2019:i:c:p:258-269

DOI: 10.1016/j.amc.2018.12.026

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