Abstract
The problem of analysis of robust stability for time-delayed neural networks with nonlinear perturbation has been investigated via Lyapunov stability theory. The sufficient conditions for robust stability of neural networks with time delays have been developed. The exponential stability criterion for neural networks is also derived. The result includes the information on the state convergence degree of the neural networks. The robust stable criterion in this paper is presented in terms of linear matrix inequalities.
| Original language | English (US) |
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| Title of host publication | Lecture Notes in Computer Science |
| Editors | J. Wang, X. Liao, Z. Yi |
| Pages | 203-208 |
| Number of pages | 6 |
| Volume | 3496 |
| Edition | I |
| State | Published - 2005 |
| Event | Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 - Chongqing, China Duration: May 30 2005 → Jun 1 2005 |
Other
| Other | Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 |
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| Country/Territory | China |
| City | Chongqing |
| Period | 5/30/05 → 6/1/05 |
ASJC Scopus subject areas
- Computer Science (miscellaneous)