| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10734195 | Chaos, Solitons & Fractals | 2005 | 7 Pages |
Abstract
We study the problem of estimating the exponential convergence rate and exponential stability for neural networks with time-varying delay. Some criteria for exponential stability are derived by using the linear matrix inequality (LMI) approach. They are less conservative than the existing ones. Some analytical methods are employed to investigate the bounds on the interconnection matrix and activation functions so that the systems are exponentially stable.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Statistical and Nonlinear Physics
Authors
Fenghua Tu, Xiaofeng Liao,