Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8960113 | Neurocomputing | 2018 | 11 Pages |
Abstract
In this paper, based on the asymptotic expansion of Mittag-Leffler function and the fractional comparison principle, an improved fractional Halanay inequality with time-varying coefficients is proved by introducing parameters λi and δ. The fractional autonomous Halanay inequality is generalized to the fractional non-autonomous case. Moreover, based on the improved fractional Halanay inequality and Lyapunov functional method, a novel sufficient condition on self synchronization of the fractional non-autonomous Hopfield neural networks with time delay is obtained. Finally, three numerical examples are given to demonstrate the effectiveness of proposed methods.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Feng-Xian Wang, Xin-Ge Liu, Jing Li,