Two-stage least squares based iterative identification algorithm for controlled autoregressive moving average (CARMA) systems

Two-stage least squares based iterative identification algorithm for controlled autoregressive moving average (CARMA) systems

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Article ID: iaor20121966
Volume: 63
Issue: 5
Start Page Number: 975
End Page Number: 984
Publication Date: Mar 2012
Journal: Computers and Mathematics with Applications
Authors: ,
Keywords: optimization, statistics: regression, matrices
Abstract:

A two‐stage least squares based iterative (two‐stage LSI) identification algorithm is derived for controlled autoregressive moving average (CARMA) systems. The basic idea is to decompose a CARMA system into two subsystems and to identify each subsystem, respectively. Because the dimensions of the involved covariance matrices in each subsystem become small, the proposed algorithm has a high computational efficiency. The simulation results indicate that the proposed algorithm is effective.

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