Global Robust Exponential Stability of Interval Neural Networks with Delays
Neural Processing Letters
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Robust stability of uncertain fuzzy Cohen-Grossberg BAM neural networks with time-varying delays
Expert Systems with Applications: An International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
BAM-type Cohen-Grossberg neural networks with time delays
Mathematical and Computer Modelling: An International Journal
Robust stability for interval Hopfield neural networks with time delay
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Expert Systems with Applications: An International Journal
A New Sufficient Condition for Global Robust Stability of Delayed Neural Networks
Neural Processing Letters
Stability analysis for discrete-time Markovian jump neural networks with mixed time-delays
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
This paper deals with the global robust asymptotic stability of the equilibrium point of class of delayed neural networks having uncertain parameters whose values are unknown but bounded. By introducing a new upper bound norm for the interconnection matrix of the neural system and employing suitable Lyapunov functionals, we obtain new delay independent sufficient conditions for the uniqueness and global robust asymptotic stability of the equilibrium point. The obtained results can be easily verified as they can be expressed in terms of the network parameters only. Some examples are constructed to compare the reported results with the related existing literature results.