| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1894173 | Chaos, Solitons & Fractals | 2006 | 7 Pages |
Abstract
This paper presents sufficient conditions for global asymptotic/exponential stability of neural networks with time-varying delays. By using appropriate Lyapunov–Krasovskii functionals, we derive stability conditions in terms of linear matrix inequalities (LMIs). This is convenient for numerically checking the system stability using the powerful MATLAB LMI Toolbox. Compared with some earlier work, our result does not require any restriction on the derivative of the delay function. Numerical example shows the efficiency and less conservatism of the present result.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Statistical and Nonlinear Physics
Authors
Haifeng Yang, Tianguang Chu, Cishen Zhang,