Global stability analysis of fractional-order fuzzy BAM neural networks with time delay and impulsive effects.

• Stability of fractional-order fuzzy BAM neural networks with impulsive effect is studied. • Suitable Lyapunov functional is constructed. • Sufficient condition for stability of fractional-order fuzzy BAM neural networks are derived. • Existence and uniqueness of solutions is also proved by using contraction mapping principle. • Various useful lemma's and fractional-order theory are applied to derive the main results. • The proposed method is analyzed by a numerical example. In this paper, the impulsive effects on the stability equilibrium solution for Riemann–Liouville fractional-order fuzzy BAM neural networks with time delay are investigated. Firstly, some sufficient conditions are derived for assuring the global asymptotic stability of the equilibrium point of the system is studied by applying the fractional Barbalat's lemma, Lyapunov stability theorem and inequality scaling skills. Secondly, the existence and uniqueness of the equilibrium point of the system are analyzed by using the corresponding property of contraction mapping principle. Two different Riemann–Liouville fractional order derivatives β and α between the U-layer and V- layer are taken into account coexistent. Furthermore, a numerical example is given to verify the validity and feasibility of the obtained results. [ABSTRACT FROM AUTHOR]