This paper considers identification problems of Hammerstein finite impulse response moving average (FIR-MA) systems and presents a gradient-based iterative algorithm and a least-squares-based iterative algorithm to estimate the parameters of the Hammerstein systems by using the data filtering technique. The analysis and simulation results show that the gradient-based iterative algorithm has a higher computational efficiency than the least-squares-based iterative algorithm.