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 (integral(t)(s) x(theta)d theta and integral(t-d(t))(s) x(theta)d theta) is proposed. Then, to further reduce the conservatism of stability criteria, one less-conservative LKF augmented integral terms (integral(t)(t-d(t)) x(theta)d theta, integral(t-d(t))(t-h) x(theta)d theta, integral(t)(t-d(t)) integral(t)(s) x(theta)/d(t)d theta ds and integral(t-d(t))(t-h) integral(t-d(t))(s) x(theta)/d(t)d theta ds) is employed, which consid- ering 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. (C) 2018 Elsevier Inc. All rights reserved.