Finite-time adaptive synchronization of fractional-order delayed quaternion-valued fuzzy neural networks

Based on direct quaternion method, this paper explores the finite-time adaptive synchronization (FAS) of fractional-order delayed quaternion-valued fuzzy neural networks (FODQVFNNs). Firstly, a useful fractional differential inequality is created, which offers an effective way to investigate FAS. Then two novel control strategies are designed. By means our newly proposed inequality, basic knowledge about calculus, reduction absurdity as well several techniques and logic, sufficient FAS criteria derived for FODQVFNNs. Moreover, settling time estimated, in connection with order initial values considered systems controller parameters. Ultimately, validity obtained corroborated by numerical simulations.