Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4631262 | Applied Mathematics and Computation | 2010 | 11 Pages |
Abstract
The paper is concerned with robust stability for generalized neural networks (GNNs) with both interval time-varying delay and time-varying distributed delay. Through partitioning the time-delay, choosing one augmented Lyapunov–Krasovskii functional, employing free-weighting matrix method and convex combination, the sufficient conditions are obtained to guarantee the robust stability of the concerned systems. These stability criteria are presented in terms of linear matrix inequalities (LMIs) and can be easily checked. Finally, three numerical examples are given to demonstrate the effectiveness and reduced conservatism of the obtained results.
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Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Wei Qian, Tao Li, Shen Cong, Shumin Fei,