A decomposition based recursive least squares algorithm is derived for the identification of input nonlinear systems using the key term separation technique and the hierarchical identification principle. The proposed algorithm avoids estimating many crossed-parameters compared with the over-parameterization identification methods and requires less computational loads. Simulation results confirm the effectiveness of the proposed algorithm.