Improved Global Robust Stability for Interval-Delayed Hopfield Neural Networks
Neural Processing Letters
A new criterion for global robust stability of interval delayed neural networks
Journal of Computational and Applied Mathematics
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Robust Stability Criterion for Delayed Neural Networks with Discontinuous Activation Functions
Neural Processing Letters
Further Stability Analysis for Neural Networks with Time-Varying Interval Delay
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Passivity analysis of neural networks with time-varying delays
IEEE Transactions on Circuits and Systems II: Express Briefs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Delay-dependent H∞ and generalized H2 filtering for delayed neural networks
IEEE Transactions on Circuits and Systems Part I: Regular Papers
A new method for stability analysis of recurrent neural networks with interval time-varying delay
IEEE Transactions on Neural Networks
On global asymptotic stability for a class of delayed neural networks
International Journal of Circuit Theory and Applications
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This paper considers the problem of global robust stability analysis of delayed cellular neural networks (DCNNs) with norm-bounded parameter uncertainties. In terms of a linear matrix inequality, a new sufficient condition ensuring a nominal DCNN to have a unique equilibrium point which is globally asymptotically stable is proposed. This condition is shown to be a generalization and improvement over some previous criteria. Based on the stability result, a robust stability condition is developed, which contains an existing robust stability result as a special case. An example is provided to demonstrate the reduced conservativeness of the proposed results.