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The global stability of fractional-order complex-valued neural networks was investigated. For a class of memristor-based fractional-order complex-valued neural networks with time delays， under the concept of the Filippov solution in the sense of Caputo's fractional derivation， the existence and uniqueness of the equilibrium point were discussed. The comparison principle and the fixed-point theorem were applied to the stability analysis through division of the complex values into the real part and the imaginary part. Some sufficient criteria for the global asymptotic stability of memristor-based fractional-order complex-valued neural networks were derived. Finally， a simulation example shows the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]