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Improved stability analysis for quaternion-valued neural networks with proportional and mixed time-varying delays

Author

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  • Cao, Yang
  • Jacob, Jincy
  • Dharani, S.
  • Sivakumar, M.

Abstract

The stability of mixed time-varying delayed and proportional delayed Quaternion-Valued Neural Networks (QVNNs) is investigated herein. We contemplate the QVNNs as a single entity, as opposed to dissecting them into separate Complex-Valued Neural Networks (CVNNs) or Real-Valued Neural Networks(RVNNs). By employing Lyapunov–Krasovskii Functionals (LKF) with free weight matrices and linear matrix inequalities (LMI), sufficient conditions for global asymptotic stability are obtained for the proposed model. To show the usefulness of the derived theoretical deductions, a numerical illustration is offered at the end.

Suggested Citation

  • Cao, Yang & Jacob, Jincy & Dharani, S. & Sivakumar, M., 2026. "Improved stability analysis for quaternion-valued neural networks with proportional and mixed time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 242(C), pages 270-278.
    • Handle: RePEc:eee:matcom:v:242:y:2026:i:c:p:270-278
    DOI: 10.1016/j.matcom.2025.11.005
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    References listed on IDEAS

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