Global Mittag-Leffler stability analysis of impulsive fractional-order complex-valued BAM neural networks with time varying delays.

• Mittag-Leffler stability of impulsive fractionalorder complex-valued BAM neural networks with time varying delays is studied. • We employed fractional Barbalat lemma and constructed complex valued Lyapunov functional. • New conditions for the existence and global asymptotic stability of the addressed impulsive FCVBAMNNs are derived. • Asymptotic stability of the equilibrium point of complex-valued systems is derived by separating nonlinear complex-valued activation functions into real and imaginary parts. • Finally, a numerical examples were illustrated to specific the effectiveness. This paper investigates the stability of impulsive fractional-order complex-valued BAM neural networks with time varying delays. As the extension of fractional-order real-valued BAM neural networks, fractional-order complex-valued BAM neural networks have complex-valued states, synaptic weights, and the activation functions. Two different kinds of activation functions are considered, along with popular bounded and Lipschitz-kind activation functions. By using Lyapunov function and Homomorphic mapping theorem, sufficient conditions for the existence of unique equilibrium and global asymptotic stability of complex-valued systems are derived. In derivation we separated nonlinear complex-valued activation functions into real and imaginary parts. Moreover, Mittag-Leffler stability for BAM neural networks(BAMNNs) have been proposed when the nonlinear complex activation functions are bounded. Simulation results are presented to prove the efficiency of the obtained methods. [ABSTRACT FROM AUTHOR]