On impulsive autoassociative neural networks
Neural Networks
Stability analyses of cellular neural networks with continuous time delay
Journal of Computational and Applied Mathematics
Exponential stability of continuous-time and discrete-time cellular neural networks with delays
Applied Mathematics and Computation
Stability analysis of a single neuron model with delay
Journal of Computational and Applied Mathematics
Delay-dependent exponential stability for a class of neural networks with time delays
Journal of Computational and Applied Mathematics
An analysis of global asymptotic stability of delayed cellular neural networks
IEEE Transactions on Neural Networks
Method of Lyapunov functions for differential equations with piecewise constant delay
Journal of Computational and Applied Mathematics
Generalized function projective lag synchronization between two different neural networks
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
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In this paper, by using the concept of differential equations with piecewise constant arguments of generalized type [1-4], a model of cellular neural networks (CNNs) [5,6] is developed. The Lyapunov-Razumikhin technique is applied to find sufficient conditions for the uniform asymptotic stability of equilibria. Global exponential stability is investigated by means of Lyapunov functions. An example with numerical simulations is worked out to illustrate the results.