Abstract: To address the problem of the large amount of computation required in the parameter estimation process of output error models, we propose a decomposition-based recursive least squares (DRLS) algorithm. The basic idea is to decompose a two-input single-output (TISO) system into three subsystems, and then identify each of the three subsystems. The DRLS algorithm is an effective method for solving large computing problems and the complex identification models of large-scale systems. We perform a simulation to verify the validity and superiority of the proposed algorithm, and summarize the characteristics of the proposed and conventional algorithms.