Recursive Algorithm of Bias Compensated Weighted Least Squares Method
Author:
Affiliation:
1. National Institute of Technology, Ariake College
2. Junshin Gakuen University
3. Professor Emeritus of Kyushu University
Publisher
The Institute of Systems, Control and Information Engineers
Subject
General Medicine
Link
https://www.jstage.jst.go.jp/article/sss/2019/0/2019_130/_pdf
Reference9 articles.
1. [1] T. Söderström: Errors-in-variables methods in system identification, Automatica, Vol. 43, No. 6, pp.939-958, 2007.
2. [2] S. Sagara and K. Wada: On-line modified least-squares parameter estimation on linear discrete dynamic systems, Int. J. Control, Vol. 25, No. 3, pp.329-343, 1977.
3. [3] M. Ikenoue, S. Kanae, Z. J. Yang and K. Wada: Identification of noisy input-output system using bias-compensated least-squares method, Prep. of the 16th IFAC World Congress, Prague, Czech Republic, July 2005.
4. [4] W. X. Zheng: On least-squares identification of stochastic linear systems with noisy input-output data, Int. J. Adapt. Control Signal Process., Vol. 13, pp.131-143, 1999.
5. [5] M. Ikenoue, S. Kanae and K. Wada: Identification of errors-in-variables models based on bias compensation of weighted least squares estimator, Proc. of the 49th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS'17), Hiroshima, Japan, pp.9-14, 2018.
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