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
Permitted and forbidden sets in discrete-time linear threshold recurrent neural networks
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
Multistability analysis for a general class of delayed Cohen-Grossberg neural networks
Information Sciences: an International Journal
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Stability analysis of multiple equilibria for recurrent neural networks
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
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In this paper, the multiperiodicity of a general class of discrete-time delayed neural networks (DTDNNs) is formulated and studied. Several sufficient conditions are obtained to ensure n-neuron DTDNNs can have 2n periodic orbits and these periodic orbits are locally attractive. In addition, we give the conditions for a periodic orbit to be locally or globally attractive when the periodic orbit locates in a designated region. As two typical representatives, the Hopfield neural network and the cellular neural network are examined in detail. These conditions improve and extend the existing stability results in the literature. Simulations results are also discussed in three illustrative examples