Global exponential stability of delayed Hopfield neural networks
Neural Networks
Existence and stability of equilibria of the continuous-time Hopfield neural network
Journal of Computational and Applied Mathematics
Stability analysis of Hopfield-type neural networks
IEEE Transactions on Neural Networks
Estimate of exponential convergence rate and exponential stability for neural networks
IEEE Transactions on Neural Networks
On equilibria, stability, and instability of Hopfield neural networks
IEEE Transactions on Neural Networks
Exponential Stability of Impulsive Hopfield Neural Networks with Time Delays
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
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In real application, the dynamics of Hopfield neural network is often affected by disturbing signals and time delays, so it is worthwhile to study dynamical properties of this type of neural network. Firstly, the ideal solution is defined as the solution of the network without disturbing signals. In order to ensure uniqueness, L"2-gain stability, global stability or global exponential stability of the ideal solution, corresponding sufficient conditions are presented, respectively, using homotopic method, inequality techniques, M-matrix properties or one time-delay inequality. All the obtained results are illustrated by several simulations.