2016
DOI: 10.1080/01969722.2016.1262709
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Stability and Exponential Synchronization of High-Order Hopfield Neural Networks with Mixed Delays

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Cited by 8 publications
(6 citation statements)
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“…On the exponential synchronization of neural networks, the previous studies [20][21][22][23][24][25][26][27][28][29][30][31] either evaluate the synchronization stability of inertial neural networks or that of high-order neural networks. The inertia item complicates the dynamic features of the neural network, while the high-order term induces bifurcation and chaos.…”
Section: Discussionmentioning
confidence: 99%
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“…On the exponential synchronization of neural networks, the previous studies [20][21][22][23][24][25][26][27][28][29][30][31] either evaluate the synchronization stability of inertial neural networks or that of high-order neural networks. The inertia item complicates the dynamic features of the neural network, while the high-order term induces bifurcation and chaos.…”
Section: Discussionmentioning
confidence: 99%
“…Ke and Li [26,27] provided the sufficient conditions for exponential synchronization of inertial neural networks and inertial Cohen-Grossberg neural networks. Brahmi et al [28] explored the exponential synchronization of high-order Hopfield neural networks. Li et al [29] considered the almost automorphic synchronization of quaternion-valued high-order Hopfield neural networks.…”
Section: Introductionmentioning
confidence: 99%
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“…Many excellent results about their dynamic characteristics have been obtained in e.g. [2,3,4,7,14,22,24,25]. Clearly, the study of the oscillations and dynamics of such models is an exciting new topic.…”
Section: An Application To Neural Networkmentioning
confidence: 99%
“…Many excellent results about their dynamic characteristics have been obtained in e.g. [2,3,4,7,14,22,24,25].…”
Section: An Application To Neural Networkmentioning
confidence: 99%