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Almost Automorphic Solutions for Quaternion-Valued Hopfield Neural Networks with Mixed Time-Varying Delays and Leakage Delays

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Abstract

This paper considers a class of quaternion-valued Hopfield neural networks with mixed time-varying delays and leakage delays. By utilizing the exponential dichotomy of linear differential equations, Banach’s fixed point theorem and differential inequality techniques, the authors obtain some sufficient conditions to ensure the existence and global exponential stability of almost automorphic solutions for this class of quaternion-valued neural networks. The results are completely new. Finally, the authors give an example to illustrate the feasibility of the results.

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Authors and Affiliations

  1. Department of Mathematics, Yunnan University, Kunming, 650091, China

    Yongkun Li & Xiaofang Meng

Authors
  1. Yongkun Li
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  2. Xiaofang Meng
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Corresponding author

Correspondence to Yongkun Li.

Additional information

This research was supported by the National Natural Sciences Foundation of People’s Republic of China under Grants Nos. 11861072 and 11361072.

This paper was recommended for publication by Editor SUN Jian.

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Li, Y., Meng, X. Almost Automorphic Solutions for Quaternion-Valued Hopfield Neural Networks with Mixed Time-Varying Delays and Leakage Delays. J Syst Sci Complex 33, 100–121 (2020). https://doi.org/10.1007/s11424-019-8051-1

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  • DOI: https://doi.org/10.1007/s11424-019-8051-1

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