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Dynamics of periodic delayed neural networks
Neural Networks, 2004This paper formulates and studies a model of periodic delayed neural networks. This model can well describe many practical architectures of delayed neural networks, which is generalization of some additive delayed neural networks such as delayed Hopfield neural networks and delayed cellular neural networks, under a time-varying environment ...
Zengrong Liu, Guanrong Chen
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On the global stability of delayed neural networks
IEEE Transactions on Automatic Control, 2003Lyapunov functional methods, combining with some inequality techniques, are employed to study the global asymptotic stability of delayed neural networks. Without assuming Lipschitz conditions on the activation functions, a new sufficient condition is established.
Qiang Zhang 0008 +3 more
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Network-Based Synchronization of Delayed Neural Networks
IEEE Transactions on Circuits and Systems I: Regular Papers, 2013 This paper focuses on network-based master-slave synchronization for delayed neural networks through a remote controller. The insertion of communication networks in a master-slave synchronization scheme inevitably induces network delays, packet dropouts and stochastic fluctuations.
Yijun Zhang 0001, Qing-Long Han
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Stability analysis of delayed neural networks
IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2000 In this paper, we derive several sufficient conditions for the asymptotic stability of delayed neural networks. These conditions ensure the asymptotic stability of the equilibrium point of a delayed neural network independently of the delay parameter ...
Sabri Arik
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Global robust stability of delayed neural networks
IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2003 This brief presents a sufficient condition for the existence, uniqueness, and global robust stability of the equilibrium point for Hopfield-type delayed neural networks.
Sabri Arik
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Stabilization of Delayed Neural Networks
2005 IEEE International Conference on Systems, Man and Cybernetics, 2006Stability analysis of delayed neural networks has been extensively developed recently. As a continuation of their previous results, in this paper, the authors propose a new methodology for the stabilization of such networks. The approach is based on the inverse optima control technique, which has been introduced to nonlinear system in the last decade ...
Edgar N. Sánchez +2 more
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Europhysics Letters (EPL), 1988
In this letter we consider the effect of random transmission delays on the dynamics of a fully connected neural network. We show that, if these delays are also present during a learning stage in which patterns are presented in succession, the network will be capable of regenerating this sequence of patterns.
A. C. C Coolen, C. C. A. M Gielen
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In this letter we consider the effect of random transmission delays on the dynamics of a fully connected neural network. We show that, if these delays are also present during a learning stage in which patterns are presented in succession, the network will be capable of regenerating this sequence of patterns.
A. C. C Coolen, C. C. A. M Gielen
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Stability of analog neural networks with delay
Physical Review A, 1989Continuous-time analog neural networks with symmetric connections will always converge to fixed points when the neurons have infinitely fast response, but can oscillate when a small time delay is present. Sustained oscillation resulting from time delay is relevant to hardware implementations of neural networks where delay due to the finite switching ...
, Marcus, , Westervelt
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