ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Global exponential stability analysis for recurrent neural networks with time-varying delay
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
A scaling parameter approach to delay-dependent state estimation of delayed neural networks
IEEE Transactions on Circuits and Systems II: Express Briefs
A new method for stability analysis of recurrent neural networks with interval time-varying delay
IEEE Transactions on Neural Networks
New stability criteria for recurrent neural networks with a time-varying delay
International Journal of Automation and Computing
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This brief is concerned with the stability for static neural networks with time-varying delays. Delay-independent conditions are proposed to ensure the asymptotic stability of the neural network. The delay-independent conditions are less conservative than existing ones. To further reduce the conservatism, delay-dependent conditions are also derived, which can be applied to fast time-varying delays. Expressed in linear matrix inequalities, both delay-independent and delay-dependent stability conditions can be checked using the recently developed algorithms. Examples are provided to illustrate the effectiveness and the reduced conservatism of the proposed result.