4.7 Article

Quasi-Synchronization and Bifurcation Results on Fractional-Order Quaternion-Valued Neural Networks

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IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2019.2951846

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Artificial neural networks; Bifurcation; Quaternions; Delay effects; Synchronization; Hopf bifurcation; hub structure; quasi-synchronization; quaternion-valued neural networks (QVNNs); time delay

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In this article, the quasi-synchronization and Hopf bifurcation issues are investigated for the fractional-order quaternion-valued neural networks (QVNNs) with time delay in the presence of parameter mismatches. On the basis of noncommutativity property of quaternion multiplication results, the quaternion network has been split as four real-valued networks. A synchronization theorem for fractional-order QVNNs is derived by employing suitable Lyapunov functional candidate; furthermore, the bifurcation behavior of the hub-structured fractional-order QVNNs with time delay has been investigated. Finally, two numerical examples are provided to demonstrate the effectiveness of the theoretical results.

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