DocumentCode :
850221
Title :
Reduced gradient computation in prediction error identification
Author :
Hill, Stacy D.
Author_Institution :
Johns Hopkins University, Laurel, MD, USA
Volume :
30
Issue :
8
fYear :
1985
fDate :
8/1/1985 12:00:00 AM
Firstpage :
776
Lastpage :
778
Abstract :
One way to design practical identification algorithms using the prediction error method is to find a computationally efficient expression for the gradient of the prediction error cost function. Here, results on adjoint equations are used to derive an efficient gradient expression which reduces the computational burden of evaluating it.
Keywords :
Gradient methods; Parameter estimation, linear systems; Prediction methods; System identification, linear systems; Equations; Filtering; Filters; Noise measurement; Noise reduction; Optimal control; State estimation; Steady-state; Time varying systems; Uncertain systems;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1985.1104062
Filename :
1104062
Link To Document :
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