Computer simulations of exponentially convergent networks with large impulses
Mathematics and Computers in Simulation
Global exponential stability of impulsive high-order Hopfield type neural networks with delays
Computers & Mathematics with Applications
Exponential Stability of High-Order Fuzzy Cellular Neural Networks with Time-Varying Delays
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
On global exponential stability for impulsive cellular neural networks with time-varying delays
Computers & Mathematics with Applications
IEEE Transactions on Neural Networks
Robust stability analysis of uncertain hopfield neural networks with markov switching
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
An impulsive delay differential inequality and applications
Computers & Mathematics with Applications
Hi-index | 0.00 |
This paper considers the problems of global exponential stability and exponential convergence rate for impulsive high-order Hopfield-type neural networks with time-varying delays. By using the method of Lyapunov functions, some sufficient conditions for ensuring global exponential stability of these networks are derived, and the estimated exponential convergence rate is also obtained. As an illustration, an numerical example is worked out using the results obtained.