Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Global attractivity in delayed Hopfield neural network models
SIAM Journal on Applied Mathematics
On the stability analysis of delayed neural networks systems
Neural Networks
Exponential stability of Cohen-Grossberg neural networks
Neural Networks
Analog integrated circuits for the Lotka-Volterra competitive neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Exponential p-stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays
Mathematics and Computers in Simulation
Dynamical analysis of Cohen-Grossberg neural networks with time-delays and impulses
Computers & Mathematics with Applications
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Asymptotic behavior of periodic Cohen-Grossberg neural networks with delays
Neural Computation
Mathematics and Computers in Simulation
Robust stability analysis of fuzzy cohen-grossberg neural networks with mixed time-varying delay
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
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We consider a class of Cohen-Grossberg neural networks with delays. We prove the existence and global asymptotic stability of an equilibrium point and estimate the region of existence. Furthermore, we show that the trajectories of the neural networks with positive initial data will stay in the positive region if the amplification function satisfies a divergent condition. We also establish the existence of a globally attracting compact set for more general networks. We estimate this compact set explicitly in terms of the network parameters from physiological and biological models. Our results can be applied to neural networks with a wide range of activation functions which are neither bounded nor globally Lipschitz continuous such as the Lotka-Volterra model. We also give some examples and simulations.