Stability analysis of delayed cellular neural networks
Neural Networks
On the stability analysis of delayed neural networks systems
Neural Networks
Exponential stability of continuous-time and discrete-time cellular neural networks with delays
Applied Mathematics and Computation
Global stability of cellular neural networks with constant and variable delays
Nonlinear Analysis: Theory, Methods & Applications
Stability analysis for neural dynamics with time-varying delays
IEEE Transactions on Neural Networks
Global stability for cellular neural networks with time delay
IEEE Transactions on Neural Networks
Time delays and stimulus-dependent pattern formation in periodic environments in isolated neurons
IEEE Transactions on Neural Networks
An analysis of global asymptotic stability of delayed cellular neural networks
IEEE Transactions on Neural Networks
Theoretical Computer Science
Existence and Stability of Periodic Solution of Non-autonomous Neural Networks with Delay
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Dynamic of Cohen-Grossberg Neural Networks with Variable Coefficients and Time-Varying Delays
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Passivity Analysis of a General Form of Recurrent Neural Network with Multiple Delays
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
IEEE Transactions on Circuits and Systems II: Express Briefs
Delay-dependent globally exponential stability criteria for static neural networks: an LMI approach
IEEE Transactions on Circuits and Systems II: Express Briefs
Almost sure exponential stability of recurrent neural networks with Markovian switching
IEEE Transactions on Neural Networks
An augmented LKF approach involving derivative information of both state and delay
IEEE Transactions on Neural Networks
Multistability in networks with self-excitation and high-order synaptic connectivity
IEEE Transactions on Circuits and Systems Part I: Regular Papers
IEEE Transactions on Neural Networks
Mathematical and Computer Modelling: An International Journal
Hi-index | 0.00 |
This paper presents new theoretical results on the global exponential stability of recurrent neural networks with bounded activation functions and bounded time-varying delays in the presence of strong external stimuli. It is shown that the Cohen-Grossberg neural network is globally exponentially stable, if the absolute value of the input vector exceeds a criterion. As special cases, the Hopfield neural network and the cellular neural network are examined in detail. In addition, it is shown that criteria herein, if partially satisfied, can still be used in combination with existing stability conditions. Simulation results are also discussed in two illustrative examples.