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Bifurcation Mechanisation of a Fractional-Order Neural Network with Unequal Delays

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Abstract

The theme of bifurcation for a class of fractional-order neural networks (FONNs) with unique delay has been incalculably elucidated. It exhibits that multiple delays are capable of increasing the complicacy of realistic FONNs, but this has been insufficiently probed into. This paper attempts to conduct a research on the stability and bifurcation for a FONN with two unequal delays. By intercalating one delay and taking remnant delay as a bifurcation parameter, the incongruent critical values of diverse delays-induced bifurcations are exactly gained. Eventually, confirmation experiments are offered to endorse the procured theory.

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Acknowledgements

The work was jointly supported by the Key Scientific Research Project for Colleges and Universities of Henan Province under Grant No. 20A110004 and the Nanhu Scholars Program for Young Scholars of Xinyang Normal University.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Xinyang Normal University, Xinyang, 464000, China

    Chengdai Huang

  2. Research Center for Complex Systems and Network Sciences, and School of Mathematics, Southeast University, Nanjing, 210096, China

    Jinde Cao

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  1. Chengdai Huang
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  2. Jinde Cao
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Correspondence to Chengdai Huang.

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Huang, C., Cao, J. Bifurcation Mechanisation of a Fractional-Order Neural Network with Unequal Delays. Neural Process Lett 52, 1171–1187 (2020). https://doi.org/10.1007/s11063-020-10293-w

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