Stability analysis of fractional-order quaternion-valued neural networks with multiple delays and parameter uncertainties

This paper proposes a fractional-order quaternion-valued neural network (FOQVNN) model with dual proportional delays, neutral delays, and parameter uncertainties. By leveraging classical lemmas and a relaxed linear matrix inequality (LMI) condition, we prove not only the uniqueness of the equilibrium point in the proposed model, but also the global robust stability of this equilibrium. Finally, numerical simulations were provided to validate the theoretical results.