Decomposition based iterative estimation algorithm for autoregressive moving average models

This paper discusses an iterative least squares algorithm for identifying the parameters of autoregressive moving average models using the matrix decomposition technique. The basic idea is to use the block matrix inversion lemma to avoid repeatedly computing the inverse of the involved data matrix at each iteration. The simulation results show that the proposed algorithm works well.