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		Erwei BAI.[en_title][J].Control Theory and Technology,2003,1(1):17~27.[Copy]

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ErweiBAI
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Outliers, inliers and the generalized least trinuned squares estimator in system identification

Erwei BAI

(Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242)

Abstract:

The least trimmed squares estimator (LTS) is a well known robust estimator in terms of protecting the estimate from the outliers. Its high computational complexity is however a problem in practice. We show that the LTS estimate can be obtained by a simple algorithm with the complexity O( N In N) for large N, where N is the number of measurements. We also show that though the LTS is robust in terms of the outliers, it is sensitive to the inliers. The concept of the inliers is introduced. Moreover, the Generalized Least Trimmed Squares estimator (GLTS) together with its solution are presented that reduces the effect of both the outliers and the inliers.

Key words: Least squares Least trimmed squares Outliers System identification Parameter estimation Robust parameter estimation