Decomposition based least squares iterative identification algorithm for multivariate pseudo-linear ARMA systems using the data filtering

This paper develops a decomposition based least squares iterative identification algorithm for multivariate pseudo-linear autoregressive moving average systems using the data filtering. The key is to apply the data filtering technique to transform the original system to a hierarchical identification model, and to decompose this model into three subsystems and to identify each subsystem, respectively. Compared with the least squares based iterative algorithm, the proposed algorithm requires less computational efforts. The simulation results show that the proposed algorithms can work well. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.