Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
412997 | Neurocomputing | 2009 | 6 Pages |
Abstract
The problem of global asymptotic stability analysis is studied for a class of cellular neural networks with time-varying delay. By defining a Lyapunov–Krasovskii functional, a new delay-dependent stability condition is derived in terms of linear matrix inequalities. The obtained criterion is less conservative than some previous literature because free-weighting matrix method and the Jensen integral inequality are considered. Three illustrative examples are given to demonstrate the effectiveness of the proposed results.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Cheng-De Zheng, Lai-Bing Lu, Zhan-Shan Wang,