Title :
An order recursive generalized least squares algorithm for system identification
Author :
Zhang, Xian-da ; Takeda, Hiroshi
Author_Institution :
Tohoku University, Sendai, Japan
fDate :
12/1/1985 12:00:00 AM
Abstract :
In system identification an order recursive algorithm is of practical interest. However, such an algorithm, for obtaining asymptotically unbiased and consistent parameter estimates in a noisy linear system is lacking. An order recursive generalized least squares (GLS) algorithm is presented. This is based on a new recursive method for computing the least squares inverse developed in Section II, and is an extension of Hsia´s GLS algorithm [2].
Keywords :
Autoregressive moving-average processes; Least-squares methods; Parameter estimation, linear systems; Recursive estimation; System identification, linear systems; Eigenvalues and eigenfunctions; Equations; Instruments; Least squares approximation; Least squares methods; Linear systems; Maximum likelihood estimation; Open loop systems; Parameter estimation; System identification;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1985.1103885
