A unified form for BELS method in colored noise case

Li Juan Jia*, Takeshi Hanada, Chun Zhi Jin, Zi Jiang Yang, Kiyoshi Wada

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

The bias eliminated least squares (BELS) method is one of consistent estimation methods for unknown parameters of transfer function in the presence of colored noise. In this paper, a unified form for BELS (UBELS) method is proposed by means of introducing an auxiliary vector and a nonsingular matrix. The introduced nonsingular matrix and auxiliary vector uncorrelated with noise are used to construct a new signal regression vector and new parameter vector. The new model described by the new signal regression vector and new parameter vector is an equivalent expression of the true system model. Consequently the estimate of colored-noise-induced bias can be obtained so that the bias of LS parameter estimate is removed to get consistent parameter estimate. It is shown that the UBELS method turns out to be a more general type of bias-correction based algorithms than the GBELS method that is recently presented. Moreover comparison between UBELS and GBELS methods and relationship between UBELS and instrumental variables (IV) methods are studied.

Original languageEnglish
Pages (from-to)2639-2644
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume3
Publication statusPublished - 2002
Externally publishedYes
Event41st IEEE Conference on Decision and Control - Las Vegas, NV, United States
Duration: 10 Dec 200213 Dec 2002

Fingerprint

Dive into the research topics of 'A unified form for BELS method in colored noise case'. Together they form a unique fingerprint.

Cite this