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Global exponential stability in Lagrange sense for quaternion-valued neural networks with leakage delay and mixed time-varying delays

Author

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  • Hanqi Shu
  • Qiankun Song
  • Jing Liang
  • Zhenjiang Zhao
  • Yurong Liu
  • Fuad E. Alsaadi

Abstract

This paper deals with the global exponential stability in Lagrange sense for quaternion-valued neural networks (QVNNs) with leakage delay, discrete time-varying delays and distributed delays. By structuring an advisable Lyapunov–Krasovskii functional in quaternion field, and adopting free-weighting-matrix method and inequality technique, a sufficient condition in quaternion-valued linear matrix inequality (LMI) to guarantee the global exponential stability in Lagrange sense is acquired, and the domain of attraction is estimated. A numerical example with simulations is supplied to confirm the availability and feasibility of the raised result.

Suggested Citation

  • Hanqi Shu & Qiankun Song & Jing Liang & Zhenjiang Zhao & Yurong Liu & Fuad E. Alsaadi, 2019. "Global exponential stability in Lagrange sense for quaternion-valued neural networks with leakage delay and mixed time-varying delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(4), pages 858-870, March.
    • Handle: RePEc:taf:tsysxx:v:50:y:2019:i:4:p:858-870
    DOI: 10.1080/00207721.2019.1586001
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    Cited by:

    1. Chen, Yonghui & Xue, Yu & Yang, Xiaona & Zhang, Xian, 2023. "A direct analysis method to Lagrangian global exponential stability for quaternion memristive neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 439(C).

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