To investigate the effect of impulsive disturbances on the dynamical behavior of the equilibrium point of complex-valued neural networks, the globally exponential stability of a class of the system with mixed delays and impulsive disturbances was studied in this paper. Assume that the neuron states, activation functions and interconnected matrix were defined in the complex domain. Some sufficient conditions for assuring the existence, uniqueness and globally exponential stability of the equilibrium point of the system were obtained by applying the M matrix theory, the mathematical induction and the vector Lyapunov function methods. Meanwhile, the exponential convergence rate was proposed. It can be concluded from the established sufficient conditions that the exponential convergence rate of the neurons is reduced by both time delays and the impulsive disturbances. The stability criteria established in this paper generalize the existing results. Finally, a numerical example with simulations was given to show the correctness of the obtained results.