Global Robust Exponential Stability of Interval Neural Networks with Delays
Neural Processing Letters
Improved global robust asymptotic stability criteria for delayed cellular neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust stability for interval Hopfield neural networks with time delay
IEEE Transactions on Neural Networks
Global stability for cellular neural networks with time delay
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
An improved global asymptotic stability criterion for delayed cellular neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
A filled function method applied to nonsmooth constrained global optimization
Journal of Computational and Applied Mathematics
Improved asymptotic stability criteria for neural networks with interval time-varying delay
Expert Systems with Applications: An International Journal
An augmented LKF approach involving derivative information of both state and delay
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
| Hi-index | 7.30 |
A novel criterion for the global robust stability of Hopfield-type interval neural networks with delay is presented. An example showing the effectiveness of the present criterion is given.