Least squares based iterative identification algorithm for output error autoregressive systems using the decomposition technique and the data filtering

This paper derives a decomposition based least squares iterative identification algorithm for output error autoregressive systems based on the data filtering. The basic idea is to use the data filtering technique to transform the original identification model to an output error model and to decompose this model into two subsystems and to identify each subsystem, respectively. Compared with the least squares based iterative algorithm, the proposed algorithm has a less computational burden. The simulation results demonstrate the theoretical finding.