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Least squares parameter estimation of continuous-time ARX models from discrete-time data

✍ Scribed by Soderstrom, T.; Fan, H.; Carlsson, B.; Bigi, S.

Book ID
121775237
Publisher
IEEE
Year
1997
Tongue
English
Weight
549 KB
Volume
42
Category
Article
ISSN
0018-9286

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## Abstract Maximum likelihood fit of nonlinear, implicit, multiple‐response models to data containing normally distributed random errors can be carried out by a combination of the Gauss‐Newton generalized nonlinear least‐square algorithm first described by Britt and Luecke in 1973, with a Fletcher