DocumentCode :
820182
Title :
Multistate least-squares parameter estimators
Author :
Mendel, Jerry M.
Author_Institution :
University of Southern California, Los Angeles, CA, USA
Volume :
20
Issue :
6
fYear :
1975
fDate :
12/1/1975 12:00:00 AM
Firstpage :
775
Lastpage :
782
Abstract :
Multistage least-squares parameter estimation algorithms which are either recursive in the dimension of an assumed linear model, or both recursive in the model dimension and sequential in time are obtained. Different aspects of the following problems are considered. 1) Given a linear model, Z(k)= K(k)\\theta + V(k) , with n unknown parameters, \\theta , and datum {Z(k), K(k)} , obtain least-square estimators (LSE\´s) which are recursive in the dimension of \\theta . 2) Given the same conditions as in 1), a new measurement becomes available at time t_{k+1} , obtain a LSE for \\theta which is both recursive in the dimension of \\theta and sequential in t .
Keywords :
Least-squares estimation; Linear time-invariant (LTI) systems; Parameter estimation; Recursive estimation; Electrons; Gaussian processes; Iterative algorithms; Nonlinear control systems; Nonlinear dynamical systems; Parameter estimation; Signal to noise ratio; State estimation; System identification; Time varying systems;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1975.1101106
Filename :
1101106
Link To Document :
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