Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409667 | Neurocomputing | 2013 | 7 Pages |
This paper considers the problem of delay-dependent stability criteria for neural networks with time-varying delays. First, by constructing a newly augmented Lyapunov–Krasovskii functional, a less conservative stability criterion is established in terms of linear matrix inequalities (LMIs). Second, by proposing a novel activation function condition which has not been considered, a further improved result is proposed. Finally, two numerical examples utilized in other literature are given to show the improvements over the existing ones and the effectiveness of the proposed idea.
► A new Lyapunov–Krasovskii functional is devised for delayed neural networks. ► Less conservative delay dependent stability criteria are proposed. ► Two well-known examples are given to show the improvements over the existing ones.