Global exponential stability of delayed Hopfield neural networks
Neural Networks
On global asymptotic stability of recurrent neural networks with time-varying delays
Applied Mathematics and Computation
Global exponential convergence of recurrent neural networks with variable delays
Theoretical Computer Science
Dynamical Behaviors of a Large Class of General Delayed Neural Networks
Neural Computation
Universal analysis method for stability of recurrent neural networks with different multiple delays
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
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In this paper, we propose a universal approach to study dynamical behaviors of various neural networks with time-varying delays. A universal model is proposed, which includes most of the existing models as special cases. An effective approach, which was first proposed in [1] , to investigate global stability is given, too. It is pointed out that the approach proposed in the paper [1] applies to the systems with time-varying delays, too.