Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6420546 | Applied Mathematics and Computation | 2015 | 8 Pages |
Abstract
This paper investigates the problem of the exponential stability for a class of neural networks with time-varying delay. A triple integral term and a term considering the delay information in a new way are introduced to the Lyapunov-Krasovskii functional (LKF). The obtained criterion show advantages over the existing ones since not only a novel LKF is constructed but also several techniques such as Wirtinger-based inequality and convex combination technique are used to estimate the upper bound of the derivative of the LKF. Finally, a numerical example is provided to verify the effectiveness and benefit of the proposed criterion.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Meng-Di Ji, Yong He, Min Wu, Chuan-Ke Zhang,