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

摘要

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.