Identification of Errors-In-Variables Models Based on Bias Compensation of Weighted Least Squares Estimator
Author:
Affiliation:
1. National Institute of Technology, Ariake College
2. Junshin Gakuen University
3. Kyushu University
Publisher
The Institute of Systems, Control and Information Engineers
Subject
General Medicine
Link
https://www.jstage.jst.go.jp/article/sss/2018/0/2018_9/_pdf
Reference13 articles.
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3. [3] K. V. Fernando and H. Nicholson: Identification of linear systems with input and output noise: the Koopmans-Levin method, IEE Proc. Control Theory and Appl., Vol. 132, pp.30-36, 1985.
4. [4] T. Söderström and K. Mahata: On instrumental variable and total least squares approaches for identification of noisy systems, Int. J. Control, Vol. 75, No. 6, pp.381-389, 2002.
5. [5] S. Thil, M. Gilson and H. Garnier: On instrumental variable-based methods for errors-in-variables model identification, Prep. of the 17th IFAC World Congress, Seoul, Korea, pp.426-431, 2008.
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1. Recursive Algorithm of Bias Compensated Weighted Least Squares Method;Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications;2019-07-31
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