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Stability of Quaternion-Valued Neural Networks with Mixed Delays

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Abstract

In this paper, we investigate the dynamic behaviors of quaternion-valued recurrent neural networks with mixed time delays. On the basis of Brouwer’s fixed point theorem, quaternion-valued variation parameter and quaternion-modulus inequality technique, some sufficient conditions are derived for assuring existence and stability of the equilibrium point of quaternion-valued recurrent neural networks with time-varying delays and distributed delays. Finally, an example is used to illustrate the effectiveness of the obtained results.

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Acknowledgements

The authors would like to thank the editor and the reviewers for their constructive comments and suggestions which improved the quality of the paper. This work is supported by the NNSF of China under Grant 61673296.

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Authors and Affiliations

  1. College of Mathematics and Physics, Jinggangshan University, Ji’an, 343009, China

    Jingwen Zhu

  2. School of Mathematical Sciences, Tongji University, Shanghai, 200092, China

    Jingwen Zhu & Jitao Sun

  3. Institute for Intelligent Systems, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

    Jitao Sun

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  1. Jingwen Zhu
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  2. Jitao Sun
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Correspondence to Jitao Sun.

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Zhu, J., Sun, J. Stability of Quaternion-Valued Neural Networks with Mixed Delays. Neural Process Lett 49, 819–833 (2019). https://doi.org/10.1007/s11063-018-9849-x

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