Global stability analysis establishes conditions for fractional-order fuzzy BAM neural networks, indicating their reliability under various delays and leakage.
A global stability analysis of fractional‐order memristor fuzzy BAM neural networks with time‐varying delays and leakage terms is covered in this paper. Sufficient conditions are established to guarantee uniform stability of fractional‐order fuzzy BAM neural networks and to derive the equilibrium point, which ensures asymptotic stability on a global scale, using the theory of fractional‐order calculus, the lemma of fractional Barbalat, and the characteristics of fuzzy logic operators. In order to validate the effectiveness of the theoretical conclusions, two numerical examples are provided to illustrate the value of the outcome.
No takes yet. Share an insight, caveat, or question.
Meenakshi et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: