Aiming at the low convergence rate and high mean square error of traditional constant modulus algorithm(CMA) and too many parameters and high complexity of traditional neural network, a complex neural polynomial blind equalization algorithm based on nonlinear Volterra channel is studied. In the studied algorithm, the complex-valued neural polynomial with a single layer neural network and nonlinear processor has very simple structure and low complexity. And the fuzzy rule controller based on fuzzy neural network (FNN) can effectively control the step-size of scale factor. The simulation results show that the proposed algorithm not only has simple structure, low complexity, fast convergence speed and small steady-state error, but also can solve the contradiction between convergence speed and mean square error.