Title :
Combining tracking and regularization in recursive least squares identification
Author_Institution :
Dept. of Electr. Eng., Linkoping Univ., Sweden
Abstract :
The combination of tracking and regularization in recursive identification is studied. It is shown that regularization of the information matrix corresponds to a normalization of the covariance matrix, and that several of the proposed methods for dealing with covariance matrix blow up can be interpreted as approximate implementations of covariance matrix normalization
Keywords :
covariance matrices; least squares approximations; recursive estimation; combined tracking/regularization; covariance matrix blow up; covariance matrix normalization; information matrix; recursive least squares identification; Covariance matrix; Equations; Least squares approximation; Least squares methods; Parameter estimation; Resonance light scattering; State estimation; Symmetric matrices; Time measurement; Vectors;
Conference_Titel :
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-3590-2
DOI :
10.1109/CDC.1996.573481
