Global convergence rate of recurrently connected neural networks
Neural Computation
Global exponential convergence of recurrent neural networks with variable delays
Theoretical Computer Science
Global Exponential Convergence of Time-Varying Delayed Neural Networks with High Gain
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
New Critical Analysis on Global Convergence of Recurrent Neural Networks with Projection Mappings
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Hopfield Neural Network for Sea Surface Current Tracking from Tiungsat-1 Data
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
A discrete-time neural network for optimization problems with hybrid constraints
IEEE Transactions on Neural Networks
Exponential stability analysis of neural networks with multiple time delays
ISNN'05 Proceedings of the Second 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
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
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Estimates of exponential convergence rate and exponential stability are studied for a class of neural networks which includes Hopfield neural networks and cellular neural networks. Both local and global exponential convergence are discussed. Theorems for estimation of the exponential convergence rate are established and the bounds on the rate of convergence are given. The domains of attraction in the case of local exponential convergence are obtained. Simple conditions are presented for checking exponential stability of the neural networks