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

• Published in: Applied mathematics and computation Vol. 349; pp. 258 - 269
• Main Authors: Gao, Zhen-Man, He, Yong, Wu, Min
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15-05-2019
• Subjects: Lyapunov–Krasovskii functional; Neural networks; Stability analysis; Time-varying delay; Stability analysis; Neural networks; Time-varying delay; Lyapunov–Krasovskii functional
• ISSN: 0096-3003; 1873-5649
• DOI: 10.1016/j.amc.2018.12.026

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.