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This paper investigates the passivity problem for uncertain neural networks with time-varying delays. By constructing proper Lyapunov functionals and using some analytic techniques, a new condition is given to ensure the passivity of the uncertain neural networks with time-varying delays. The passivity condition is expressed in terms of linear matrix inequality (LMI), which can be easily solved by...
In this paper, the global exponential stability is investigated for a class of neural networks with both discrete and distributed delays and norm-bounded uncertainties. The discrete delay considered in this paper is interval-like time-varying delay. By using Lyapunov stable theory and linear matrix inequality, the derived criteria are not only dependent on distributed delay but also on the lower bound...
This paper investigates the robust stability of uncertain neural networks with time-varying delays and Markoian Jump parameters. The norm-bounded uncertainties are included in the system matrices. The constraint on time-varying delays is removed, which means that a fast time-varying delay is admissible. Some new delay-dependent stability criterions are presented by using Lyapunov-Krasovskii function...
The robust state estimation problem for a class of uncertain neural networks with time-varying delay is studied in this paper. The parameter uncertainties are assumed to be norm bounded. Based on a new bounding technique, a sufficient condition is presented to guarantee the existence of the desired state estimator for the uncertain delayed neural networks. The criterion is dependent on the size of...
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