Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
408686 | Neurocomputing | 2010 | 11 Pages |
Abstract
The problem of robust exponential stability for a class of discrete-time recurrent neural networks with time-varying delay is investigated. By constructing a new augmented Lyapunov–Krasovskii functional, some new delay-dependent stable criteria are obtained. These criteria are formulated in the forms of linear matrix inequality (LMI). Compared with some previous results, the new conditions obtained in this paper are less conservative. Three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed method.
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Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye,