Convergent activation dynamics in continuous time networks
Neural Networks
Exponential stability of Cohen-Grossberg neural networks
Neural Networks
Exponential stability of continuous-time and discrete-time cellular neural networks with delays
Applied Mathematics and Computation
Harmless delays for global exponential stability of Cohen-Grossberg neural networks
Mathematics and Computers in Simulation
Neural Processing Letters
Exponential Stability of Discrete-Time Cohen-Grossberg Neural Networks with Delays
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Periodic Solution of Cohen-Grossberg Neural Networks with Variable Coefficients
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Global stability of a class of Cohen-Grossberg neural networks with delays
International Journal of Intelligent Systems Technologies and Applications
IEEE Transactions on Circuits and Systems Part I: Regular Papers
IEEE Transactions on Neural Networks
Stability analysis of discrete-time recurrent neural networks with stochastic delay
IEEE Transactions on Neural Networks
Stability of equilibrium solution and periodical solution to Cohen-Grossberg neural networks
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
Dynamics of an adaptive higher-order Cohen-Grossberg model
Neurocomputing
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Discrete-time versions of the continuous-time Cohen-Grossberg neural networks (CGNNs) are formulated and studied in this paper. Several sufficient conditions are obtained to ensure the global exponential stability of the discrete-time systems of CGNNs with and without delays based on Lyapunov methods. The obtained results have not assume the symmetry of the connection matrix, and monotonicity and the differentiability of the activation functions.